{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Agent-based Modeling: Covid-19"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This notebook contains an implementation of our Covid-19 simulation using agent-based modeling. We want to demonstrate how the spread of the virus affects our society. The model was implemented using [BPTK_Py](https://bptk.transentis-labs.com/en/latest/docs/api/api_overview.html#). This framework not only enables us to do agent-based modeling, it can also manage simulation scenarios easily."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from BPTK_Py.bptk import bptk\n",
    "\n",
    "bptk = bptk()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "With this model, the goal is to figure out the amount of people a person infects over a certain period of time. We call this value the reproduction rate `R0`. Assuming `R0` is 2. The following picture shows how the virus spreads.\n",
    "\n",
    "\n",
    "![Image](images/r0.png)\n",
    "\n",
    "We want to make assumptions which reflects the current situation in Germany.\n",
    "\n",
    "__Assumptions__\n",
    "\n",
    "- __Contact Rate: 20 persons.__ Defines how many people a person encounters per day in average.\n",
    "- __Infectivity: 0.7%.__ Defines the probability that a person becomes infected after contact with an infectious person.\n",
    "- __All__ people can get infected.\n",
    "\n",
    "Each person is equivalent to one agent. Each agent can have the following states: `HEALTHY`, `INFECTED WITH NO/LIGHT SYMPTOMS`, `INFECTED WITH STRONG SYMPTOMS`. Usually, if someone gets infected and realizes strong symptoms, he stays at home to rest. Therefore nobody can get infected by this person. People with light or no symptoms are still able to leave the house. These are the ones who continue the chain of infection. We implement this scenario into our model."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Base Scenario"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The base scenario presents the results of the above assumptions. Instead of 80 million agents we only create 8,000. Running 80 mio. agents through the model would take forever. However, it won't falsify the results. Before we analyze the results, we first need to understand the process of the simulation.\n",
    "\n",
    "![Image](images/abm_diagram.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "1. The simulation creates a number of agents and determines their states randomly. We have to keep in mind only a few agents are infected. In reality, the spread of the virus starts with just a few people until it reaches the majority of the population.\n",
    "2. The state of every agent is checked. Clearly, `HEALTHY` agents don't infect other agents. The same scenario applies to agents `INFECTED WITH STRONG SYMPTOMS`. They \"stay at home\".\n",
    "3. Infected agents with light/no symptoms meet other agents.\n",
    "4. Only `HEALTHY` agents can get infected, since the other agents ars.e already infected. The infectivity determines the probability of an agent to get the virus. The higher the infectivity the higher is the possibility of getting Covid-19. In other words, not every `HEALTHY` agent gets the virus after contact with an infected agent.\n",
    "5. The `HEALTHY` agents change their states. A majority of the agents is only `INFECTED WITH LIGHT/NO SYMPTOMS`. However, a few agents can get `INFECTED WITH STRONG SYMPTOMS`.\n",
    "6. We check if we have reached the last round of the simulation. If not, we go back to `STEP 2`."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Development of society with Covid-19"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The following plot shows the number of agents who are healthy, infected with no/light symptoms and strong symptoms for each day. In this simulation, every agent will get infected. It remains infected indefinitely. However, it won't falsify the result of our simulation. As we explained before and shown in the plot below, most of the agents have only light or no symptoms. According to the plot, the curve of the infected agents with no or light symptoms grows exponentially. With social distancing, we can flatten the curve. This topic will be explained in another blog post, though (see [Covid-19 and the SIR-Model](https://www.transentis.com/covid-19-sir-model/))."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "5ad0c0b4fd7e45cf8f9ca31d4e2c6400",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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Ba+2KBMc1QDbO5/5Hofc1/QcYE1oiLCIi7YgSXCIiIq3n/zXhmDRwZhcQW0z89dCT4ZoiOsHVEafGzPP19HcnOL5+n2hdi6lOcIXtBl5JcJwjQ6+GzLLWLkpw7DbLWmuNMXcCryc7lig9Q69E1FsLylq70BizBae4fjh51gO4PPSqjxd4FPhHgjG1lL4kvjyyvp9hTRl3LfAkMD9Uv01ERNoZLVEUERFpm07D+eM07KWmDmSt/RdaptievQTUnHH3f42sx/Ya8Huq61DV50NguLX2jgZ7tjPW2jeA1cmOo7VZa98HBgDjcK7X38Ahm3AK8R9urb3BWrunlUNMNi9QCHwFrAH+CEwCfmyt/R9r7RNKbomItF/G2kRWIIiIiIhIe2SM6QIMBA4B8nFm3pUBXwN/t9Z+m8TwpBUYY3KBnwAHAl1wZmeWAN8Cn1hrv0tieCIiIi1KCS4REREREREREWnXtERRRERERERERETatTaZ4DLGXGCMWWuMKTPGfGuMWWiM6dGI4/JCj8IuNsbsNsY8a4zpHKffOcaYT40xlcaYdcaYXzd1LBERERERERERSa42l+AyxowAngP+CpwD3IrzFKrXjDENxbsE53HHl+MU0D0WWFZj/CHA/wHvAmfgFF99zhgzPNGxREREREREREQk+dpcDS5jzPM4T3L5n6i2EcBfgH7W2vV1HHcCTlLs5NATZDDGHAd8DJxmrV0ZansLSLPWnhp17OtArrV2SCJjiYiIiIiIiIhI8qUmO4A40oDdNdpKQl9NPcedAewIJ6QArLVrjDGbQ/tWGmPSgVOAa2sc+zww3xiTZ63d3Zix6ruALl262F69etXXRUREREREREREEvCPf/yj0FrbNd6+tpjgehpYZoy5BGdJYHdgJvCOtXZdPcf1BTbEaV8f2gdwKE4CrWa/9TjLNfsAf2/kWHXq1asXn3zySUPdRERERERERESkkYwxX9e1r80luKy1rxljxgJPAc+Emv8KjGjg0E5Uz/SKVgwcEtWHOP2Ka+xvzFh1CgaDeDyehrqJiIiIiIiIiEgLaItF5k8BHgcexFlOeAGQDyw1xqQkM7b6GGMmGGM+McZ8smvXrmSHIyIiIiIiIiKy32hzM7iAB4CXrbW3hhuMMf/CWTJ4DvDnOo4rBuKtw+xE9Qyt8Ne8OH2o0a+hsWJYa58EngQ45phj2lblfhERERERERGRfVhbTHD1BZ6LbrDWfm6M8eDU0KrLBuCkOsZbFnq/CfCF2t6r0ScIbExgrDq5XC4yMzMb6iYiIiIiIiIiIi2gzS1RBL4GjoluMMYcCWQCW+o57g2guzFmSNRxg3FqZr0BYK2tAt4FflXj2F8DH4WeoNiosUREREREREREpG1oizO4Hgf+YIz5DieZ1A34DU5y6/VwJ2PMKgBr7dDQ14+MMcuBhcaYm3BmZP0OWG2tXRk1/gxglTFmLs5srDNDr9PDHRIYS0REREREREREkqwtzuB6CLgaOA34CzAb+BfwM2tteVS/LGBnjWN/jbP08GlgIfAPYFR0B2vtauA8YBjwFs7TGUdba5cnOpaIiIiIiIiIiCSfsbb91UM3xqQDpcBwa+17DfXf2wYPHmw/+eSTBvuVlpayc+dOfD7fXohKRNqrtLQ0DjjgAHJzc5MdioiIiIiISNIYY/5hrR0cb19bXKLYGIOBT9ticquxSktL2bFjBwUFBWRmZmKMSXZIItIGWWvxeDx8++23AEpyiYiIiIiIxNEWlyg2yFr7YV0Zu/Zi586dFBQUkJWVpeSWiNTJGENWVhYFBQXs3FlzVbaIiIiIiIhAO01w7Qt8Ph+ZmZnJDkNE2onMzEwtZxYREREREamDElxJpJlbItJY+nkhIiIiIiJSNyW4RERERERERESkXVOCS0RERERERERE2jUluEREREREREREpF1LTXYAUm3VZ18mO4RahvY/LNkhtFtjx45l8eLF+P3+SNvQoUN57733OPnkk1m1alWtY1JTUxkzZgwLFiwAYMuWLfTu3Tvu+Hl5eZSUlAAwbdo07rnnnjpjWbFiBcOGDYtpe+utt3jsscf429/+RlFREbm5uRxzzDFcdNFFjBkzhssuu4xnnnmmwevs2bMnW7ZsSSiGXr168fXXXwNObamcnBwKCgo47rjjGDt2LEOHDm3wvDWtWrWKU045hUWLFjFmzJg6+/Xq1YvDDjuMlStXxrRba1myZAkLFizgH//4B8XFxeTk5DBgwABGjBjBFVdcQV5eXoPjQPX3bcaMGdx5550x11ufSy+9NPK9FxERERERkcZTgquNKav0UuapSnYYZGemk53hTnYY+6z33nuPd955h1NPPbVR/c877zzOOeecmDa3u/b356GHHqJTp0612gcMGBB5b63lmmuuYd68efTv359JkyZx8MEHU1xczIoVKxg3bhzffvstV155ZUxSbP369dx3331MmjSJE088MdKenZ2dcAwA/fv357bbbgOgrKyMjRs3snTpUp555hkuvvhi5s+fT0pKSn23pcVUVVVx/vnn8/LLL3Pcccdx3XXX0aNHD3bv3s1HH33EnXfeydKlS/nwww+bNP7cuXMpKyuLbP/5z39m6dKlte7VoYce2uxrERERERER2R8pwdXGlHmq2L67NNlh0J3cNp3g8ng8pKen43K1v1W2PXr0wO/3c/fddzc6wTVw4MB6ZyWFjRo1ioMOOqjePg899BDz5s1j4sSJPProozH38MYbb+Tjjz9m/fr1nHDCCZxwwgmRfatWreK+++7jxBNPrDeWxsQA0L1791rjzJ49m6uvvponn3ySgw8+mHvvvbfBcVrCzTffzMsvv8ycOXO46aabYvZNmTKF7du38/TTTzd5/JEjR8Zsf/nllyxdurTR90pERERERETq1/6yA/uJo3sVJO3VXNOmTcMYw3//+18uvfRSOnXqRG5uLhdeeCE7d+6M6bt27VpGjBhBp06dyMzMZPDgwSxbtiymz4IFCzDGsHLlSm644QZ69OhBhw4dKC0tJRAIMGvWLPr27UtWVhYdO3Zk0KBBPPbYYzFjbNu2jTFjxtC1a1cyMjIYOHBgraVgW7ZswRjDzJkzWbhwIX379iU9PZ2jjjqKFStWNPu+hGVmZnLrrbeyevVqli9f3mLjNkZlZSUzZ87k8MMP56GHHoqbIDz++OMZO3bsXo0rLDU1lUcffZQjjjiCBx98kNLS1k/2fvvttzz22GOcdtpptZJbYd27d+eOO+5o9VhERERERESkaTSDS1rNmDFj6Ny5MzNmzOCLL75g3rx5rF+/njVr1uB2u/nggw8YPnw4/fr1Y+rUqWRkZLBkyRJGjRrFn/70Jy688MKY8aZMmUJOTg633norFRUVuN1upk+fzvTp0xk/fjw33ngjHo+HdevWsXr1aiZNmgRAYWEhJ554Irt27WLy5MkUFBSwZMkSxo0bR2FhYa2kxtKlSyksLGTixIlkZmYyd+5cRo0axdatW8nPz2+RezNp0iTuv/9+7r77boYPH95g/4qKCgoLC2PasrOzycjIiGkrLi6u1QbQpUsXAFavXk1hYSHXXHMNaWlpzbiCujUUQ0NSU1O56KKL+M1vfsPq1as588wzWzrEGG+88QZ+v59LLrkk4WN9Pl+t7ws490BERERERET2HiW4pNXk5+ezfPnySB2lAQMGMGHCBObPn8+ECROYMGECxx57LO+++26kz9VXX81JJ53ELbfcwgUXXIAxJjJeeno677//fkxi5uWXX+bMM8/kqaeeqjOO3/72t3zzzTe8+eab/PznPwecBNPJJ5/MXXfdxbhx4+jcuXOk/5dffsnGjRvp1q0b4BSGHzRoEM899xxXX311i9ybzMxMbrvtNq677jpef/31BpM4s2bNYtasWTFtjz32GBMnToxp+/GPfxz3eJ/PR2pqKuvWrau3X0toKIbGCNfr+vLL1n/wQvie1KwR5vf7I0X8w/Lz82Nmvb3//vt07dq11WMUERERERGR+inBJa1m8uTJMUXCx44dy80338yrr77K8ccfz4YNG5gyZUqt2S5nnnkmU6dOZePGjRxxxBGR9iuuuKLWrKOOHTvy2WefsX79eo488si4cbz66qsMGDAgktwCSEtL4/rrr+f888/n7bff5vzzz4/sO/fccyPJLYCjjz6a3Nxcvvrqq6bdiDpceeWVzJ49m2nTpjWY4Bo7diwXXXRRTFu8633uuefizpQKfx/CS/5yc3ObGnaDGoqhMXJycgDYs2dPi8VVl/A9CZ8z7G9/+xsnnXRSTNu2bdtiamYNGjSI2bNn1xpzx44djaqZJiIiIiIiIi1DCS5pNdHJKXCSSocccgibN29m48aNAEycOLHWLKSwnTt3xowR7wlzM2fO5JxzzqFfv3706dOHYcOG8atf/YqhQ4dG+mzZsoURI0bUOrZfv34AbN68Oaa9Z8+etfp26tSJoqKiOq60adLT07n99tu55ppreOWVVzj77LPr7HvooYfGPNGwLkOGDKm3aHk4sdWaiaOGYmiMcHw1k06toa57El17beHChSxatKjWsfn5+XG/L1u2bGn5QEVERKRVWGudV+R9siOq5kRFTEw2aqMpocYcX8dY4fa2dC+awhJ9reGvzbt/0WPEfF8i36t2ftNkr4j/2Yne3/zP6f5ICS5JimAwCMB9993HscceG7dPzSVjmZmZtfr89Kc/ZdOmTbz22musXLmSZcuWMW/ePK688koef/zxJsVW10yj1vg/qyuuuILf/e53TJs2rd4EV0sJz/r6z3/+U+vJfm3Jf//7XwAOO+ywVj9X+J58+umnHH300ZH2vLy8SPJq9erVrR6HiIhIYwSDwZhEjMX5GgwnaWokaqL/cArvI87+YNBGxqo5RtAGI32DQZvQ70TBSIyWYBCCOGMRGjdYY9zweZ14os4djiXcFxv5qy8YSTZEXV8w1EbU+a1zneHzBoNB59hwDG0wqRPvj+DY/U0LNl7ih5hz1X/e9iL29tSf7Epo3LjnUkJCGs/a+P/BRX5mx/TdOzG1G6nuDnXu2ptxyP7l888/j8ySAqcG0+bNmxkyZEgkcdGhQ4dGzUyqT15eHqNHj2b06NH4/X7Gjh3LE088we23307Pnj3p1asXGzZsqHXc+vXrAejdu3ezzt8cbrebqVOnMnHiRJYuXdrq5xsyZAj5+fk8++yz3HHHHY2uibU3+f1+nn32WTp06MCQIUNa/XxnnHEGqampLFy4kIsvvrjVzyciIq0jEAyGkhjxkjShZEmNJE4w/ArWfO8kPvz+IAEbJBB02gPBYCTB4vR1EiXR5w7a6nMCNZJM8RMw4SROJHaqEzzhsaITMTEJrFrjx2t3zhT9R33N2TrhMauTPVH7bLw/ufYtMfesDV1mTCIqdkfttiaMDvH/eN7XkzUtOYsr3gD74j2TlhfvU2hjfzjH6SEYU+cfsW3vr1vZZzz88MOMGDEiMiNqwYIFlJSUcNZZZ3HMMcdw+OGH88ADD3DJJZfQsWPHmGN/+OGHRhXv3rVrV0yB+NTU1MjMr5KSEnr27MnZZ5/N/fffz4oVKzjttNMAJ4kyd+5cMjIymp1ga67x48fz29/+lmnTprX6uTIzM5k6dSo33ngjU6ZM4aGHHoopmg7w97//nc8++4yxY8e2ejw1+f1+rr76aj7//HPuuOOOVq0VFnbQQQcxYcIE5s2bx/3331/rqZqgqeYiIi0lnKgJBMNJI+drZNtWb4f7+fwBqvwBfIEAPn8Arz+ALxDE5/fjDQTw+YP4AoHIbJyayZ1w8iict4iZpRROfFmLDVqC4dlQwWCbnbVSfX0AUcmnmLZw39pXEZPMCh0X/hJzfHSyLHJwdYItsZjjnavmH3RRSwNt7T7h/XFzCnH+CIw51sa21fyMgMVgCP0Poh5y1BaYGl+dDVNrf5PHj3O9bewWNIuJukPxrss09Q6amC8xjfvS/ZPWY+JsNPnzuD9xueos7qwEVxv1ry3fJjuEZisqKmL48OGMGjWKL7/8kkcffZSjjjqK8ePH43K5mD9/PsOHD6dfv36MHz+enj17smPHDj7++GPWrVvHpk2bGjzHkUceyZAhQzj22GPp1q0bn3/+OY888ggDBgzgqHiGvtgAACAASURBVKOOAuDWW2/l+eefZ+TIkUyePJmCggJefPFFPvzwQ+bMmUN+fn5r34p6paWlceedd3L55Zc3e6ylS5fSqVOnWu3HHXccffr0AeD666/n888/59FHH+W9997j/PPP56CDDqK4uJh33nmH119/nXvvvbdVYwDYvn07ixcvBqC8vJyNGzfy5z//mS1btjBmzBimT5/epPP/5S9/iVsD6xe/+EXMEsRoDzzwAF9//TU333wzL774Iueccw4HHnggRUVFrF27lpdeeokuXbqQlZXVpJhERNoyay3+QJBAMIg/GPoaCEZmM4WTTeGEk9/v9PMHncSSPxAkEIg6NuhsB4IWfzAYGSMQeh8zA8oGnWVrkdlQtlafxv67tTMDiurEDFQnSuIsYYPqxFYk8RWa4RWMJMSqZ04F482GimqPTsDUiriOf4W31ZmXOAmf6GROVOYHqpMxxvlTKJyUiSRCjIn5A9tQezv2j3Nnvwk1VPc3tdpcNcZqDGNSnDhDx7lcxhkPMC6n0WWqv1af22BczjtXuC36uk047toJjOh2EzO2M5bLGIzLhSsUT/U9SPz6WpuJk8yKl5RqmXFjejT7HMkU+Sw0kOBy2hO/1ugj9vUkobSOuj+bSpTWZcO3O+vdrwRXG5OdmU53Wn/WSmPiaK7Fixcze/Zs7rrrLvx+P7/85S958MEHcbvdgFM/a82aNcyYMYMnn3ySkpISunXrxsCBAxudYLn++ut55ZVXeOCBBygrK6OgoIDLL7+cqVOnRmYmdenShQ8//JDbb7+dP/7xj+zZs4cjjjiCp59+mnHjxjX7OlvCpZdeyqxZsxqV1KvPtddeG7f94YcfjiSXjDE88cQTnHPOOTz++OM88sgjFBUVkZuby+DBg1m0aBEXXnhhq8YA8Nlnn3HxxRdjjCE7O5uCggJOPvlknn76aU455ZQmn/+ll17ipZdeqtXevXv3OhNcGRkZvPzyyzz//PM888wz/OEPf6CkpIScnBz69+/PzJkzufzyy+Mm7kREkiEYmeFkIwmp8CwofzDgfA0ln6r8fnz+IJU+Hz5/EG8ggNfvx+t3voaX4QWDELAB52tUUiu8DC+yTK6ZM5uCwerEUXWNJxs1iwpseDYWsbOrqpcGVi/bC78iCZSopE/4j87qr04MJiZR4iQ8ovuaUALEhSEtJQWXC4xxRZIvLmMi7w0ujAtSnJOHkjcOlyuSPoq5B5FET8w5TeQaTPQ44aRMdL8aiRgTiicyVuQcsQmg6P7UuEfheGKPqxmb/toSEZG2y2jpTcsbPHiw/eSTT+rts379+khx67BVn33ZmmE1ydD+iRf5njZtGvfccw/btm1r9tP0RKRavJ8bItI+BYNBqkIJpiqfk2yq9Poo9/qo9PoiCStvIBCZDeXzByKzpIJBSyCqblMgECRgY5f2hWtJNUYgCNZGzaCKrmUVmtkUTjjZGvucZFN46Z+NzKIKUl3PKRwn2EgyxkQlierbdrlcpLpcpKWkkOIypKY426kpKc77lPC+6gRUzYRMvBk/4X41zxnuF94WERGRtuHTrd9z7aifb7aVFYfE268ZXG1IU5JJIiIi0nb4QkkrXyAYNUsqQHmll4oqL3uqvFRUVVFR5SSxfOHaUgGnrlQis6OCQWrNYopJUAWdBFigZuIqzuwnlwFXKEHkiklARSWFovalpaSQkuIixeVsp7gMqa4UTOh9isuFy0Uo6eQi1eUkqlJcJmYc55zgMi5cruj22DhEREREGqIEl0iCtm/fXu/+lJSURhXIl8bZvXs3Ho+n3j75+fmRpa8iIi3JWhtT3Lz65aeiykdFlZfyKi8en4+KKl+kJpU/EK5P5WzHK8sdCNhILavIMsNQLavwbKdIEovY5XzRM6FqJoTC28YYUowhPSWVtBQXqakuUlwpuFOc2U/uVGfmU2pKCq5wUso4X8OJq/C4xijhJCIiIm2bElwiCTrwwAPr3d+zZ8+4Rc6laa677jqeeeaZevu8++67DB06dO8EJCLtWjAYxBcI4g/NmAonpHyBAF6fn3Kvk7TyVPmo8PrwVPnwBvzOEsGovv46Zls5daxiE1WRAu41vqa4DCmR5XYuUlwustLTSE9LjSzLC8+GSom8d7ZTU1yRpFN0YsrlMrWSVEpIiYiIyP5ACS5pcdOmTWPatGnJDqPVrFixot79mZmZeymS/cMtt9zCmDFj6u0zcODAvRSNiLRV/kCASp+fSq+fKr8fT5WXskpndpXT7nNqXvn8BKyTZAo/7c8fKs4eCAbijh0uuh6eaRUu7O7UvQonrZw2sFEJKRepKU6yKSMtjYwOKWS63WSmpZLhTsOdmhKaQeXCnRqaSaVklIiIiEiTKMElkqBhw4YlO4T9Sr9+/ejXr1+ywxCRJPP6neRVpc9Hpc9PRaVTz6q0opI9nkoqvf4aTwcMUFc9KydB5dSoCoRqUkUKt0cvGQy1hZNW4VlW4VlUmelppKelkJ6aRkZaKhnuVNypqaGi584ywLSU6mSXiIiIiLQeJbhEREQk6eIlsHZ7Kin1VDkJLJ/fSV75AnhDta2iWYtTzypQvQQxXAsr5smC1kYVRg8t43MZUozzPis9DXdaCplpaaS7U8lISyMtlKhKjXx1abaViIiISBujBJeIiIi0KmstVT4/lT5/6KuP8iovezxVjU5gBYPhBFYgpoZWIBjA53eWDaammMiSv9QUFx0y0sh0p+FOSSE9LRV3akpkhlV0XavUlHC9K5fqVYmIiIi0U0pwiYiISIvw+QPsqayitKKSUk/4VUV5pTcmeeX1B2rVu7KWmMRV7NcA1tqoGVRO7aqczHQy09LISneTlZ5GWmpKKInl7NeyQBEREZH9hxJcIiIikrBgMEh5lZdSTxXF5RVsL97DrrIKKqq8VFR58dWYgRUIEklWBQJBfMHqZYROAosataucBFZWupsO6aGZWKmpMQkszbYSERERkTAluERERKRe1loqfX72eCrZXVHJzt172Lm7nLJKLxVeLx6vj3BBd68/GFqK6MPvr05kGRNOYKWQ6nKSWLlKYImIiIhIC1GCS0RERCJ1sjxeHx6vj4oqL7srKiku91DqqQy1+6mo8hK0QcB5GmGlz0+V16mvVen3k5ZinCcKprnJyk6jQ2j5oFMDKzWSvEpLUb0rEREREWk5SnCJiIjsZ7x+P7srKimtqIwksXZXePB4fXh9Aar8TjF4G5qVBU6Rd2+ovTL0xEOLDSWzUjmwUw6dsrPIyXCTle4mIy1VCSwRERER2WuU4GpDvvvug2SHUEuPHiclOwQREWmmKp+f3RUeiss8fFdcys7SMsorvZRXeWOKvQeD4AsE8PmdWlnhpxl6/QEskJ6aQkZaGh2zMsk/IJPcrAyy3M4MLRV0FxEREZFkUoKrjfH5yvD7y5MdBqmpHUhLy052GO3a2LFjWbx4MX6/P+7+Xr16cdhhh7Fy5cpIW32zHX7605+yevXqWu1//vOfOffcc+ncuTPff/89aWlptfoMHTqUb775hi+//LLWvsrKSjIzMxtzScyaNYvbbruN7t27M3jwYF599dVafTZs2MCRRx7JnDlzuOmmm5gwYQJPPfUUf/3rXzn++ONr9f/1r3/NsmXLWLt2Lf37929UHCJSv0qvj5IKD8VlFXxXXMoPpaF6WVHLC73+AJ4qH1WhZJbPHyCIJS3FFVlGmJORTk5GOtmZbjLdzqysrHSnVpaIiIiISFui31DbGL+/nIqKnckOg6ysA5TgSpKhQ4dy2WWX1Wo/4IAD4vZftGgRvXv3ZvPmzbzxxhuMGDEiofO53W4WLVoU0/boo4/yz3/+kz/+8Y8x7YMGDUpobIA5c+bw2muvccUVV7B27VpSo/4wfv3111myZAl33323klsizRCul1VUVs53xXvYVVpOWVUV5ZXeyDLDKl8gUl+ryu8n1eUi051GdoY79HIKvqenpZKemkJ6WqpmZYmIiIhIu6EEVxvVufNRSTv3rl2fJu3cjeXxeEhPT8e1D/7xdeihhzJmzJhG9S0qKuL111/n97//PfPnz2fRokUJJ7hcLlet87366qt8+umnjY6jPnl5eTz66KOMGjWKOXPmcPvttwNQXl7OVVddRb9+/bjjjjuafR6R/YW1lvIqLyXlHnbtKee74lKKyz2UeaqoCD3N0FpnWWKlz4enyqmZ5U51ElpdczvQJbeDMzMrI530NP0qICIiIiLt376XHZCkmzZtGsYY/vvf/3LppZfSqVMncnNzufDCC9m5M3Z22tq1axkxYgSdOnUiMzOTwYMHs2zZspg+CxYswBjDypUrueGGG+jRowcdOnSgtLSUQCDArFmz6Nu3L1lZWXTs2JFBgwbx2GOPxYyxbds2xowZQ9euXcnIyGDgwIEsWLAgps+WLVswxjBz5kwWLlxI3759SU9P56ijjmLFihWtcq+a64UXXiAYDHL++eczevRoXnnlFUpKSpIdVi0jR47kvPPOY/r06ZFlknfddRfbtm3jqaeewu12JzlCkbYrGAyyu8LD1sJi/vHVNl5du45la/7La2vX8+5nX/L5dzvZUbKHXWUVFJVV8F3RHr7+oZhdZeUEreWAjtkM6l3ACX16MaRvbwYfejC9uubTOaeDklsiIiIiss/Qb7bSasaMGUPnzp2ZMWMGX3zxBfPmzWP9+vWsWbMGt9vNBx98wPDhw+nXrx9Tp04lIyODJUuWMGrUKP70pz9x4YUXxow3ZcoUcnJyuPXWW6moqMDtdjN9+nSmT5/O+PHjufHGG/F4PKxbt47Vq1czadIkAAoLCznxxBPZtWsXkydPpqCggCVLljBu3DgKCwu56aabYs6zdOlSCgsLmThxIpmZmcydO5dRo0axdetW8vPzE74PhYWFcduDwWDc9qqqqrjHZGVlkZWVFdO2aNEihg0bRteuXbngggu4+eabefHFF7niiisSjjNRPp8vbpx1Jdgefvhh3n77ba688kpmz57NQw89xDXXXMNPfvKT1g5VpN3xBwIUlVWwvcRJVhWXeyirrMIbqukXCEKVz1luWOlznnyY7k4l051G907ZdMnpQHZohpY7NSXJVyMiIiIi0vqU4JJWk5+fz/Lly0lJcf64GjBgABMmTGD+/PlMmDCBCRMmcOyxx/Luu+9G+lx99dWcdNJJ3HLLLVxwwQUxRdfT09N5//33Y4qov/zyy5x55pk89dRTdcbx29/+lm+++YY333yTn//85wBMmjSJk08+mbvuuotx48bRuXPnSP8vv/ySjRs30q1bN8CpiTVo0CCee+45rr766oTuQSAQoGvXrnXu79OnT622xYsXs3jx4lrtU6dOZebMmTFxfvTRR5H6WT169GDo0KEsWrRoryS4li9fXu+11dS9e3ceeOABxo8fz89//nMOOugg7r333laMUKR98fkD7Cor5/viUr7+oYTisgpKPZVYLIGAdepn+Xx4vH6CwSAZ7lQy0tI4uHMn8rMzyclMp0O6m9QUJbREREREZP+jBJe0msmTJ0cSV+A8VfDmm2/m1Vdf5fjjj2fDhg1MmTKF4uLimOPOPPNMpk6dysaNGzniiCMi7VdccUWtJwR27NiRzz77jPXr13PkkUfGjePVV19lwIABkeQWQFpaGtdffz3nn38+b7/9Nueff35k37nnnhtJbgEcffTR5Obm8tVXXyV8D1wuF2+99VbcfXXVtzrjjDO44YYbarX37t07Znvx4sVkZWUxcuTISNvo0aO54oor2LJlC7169Uo43kQcf/zxMQm3sG3btjF+/Pi4x4wbN45Fixbx7rvvsnDhQrKz9SAD2b95/X4KS506WlsLnZlaezxVgMUXCFJeWUV5lRd/wJIZmqFVkJ9Hpw6ZdMhw0yHdrULwIiIiIiIowSWtKDo5BU5S6ZBDDmHz5s1s3LgRgIkTJzJx4sS4x+/cuTNmjEMPPbRWn5kzZ3LOOefQr18/+vTpw7Bhw/jVr37F0KFDI322bNkSt/B6v379ANi8eXNMe8+ePWv17dSpE0VFRXVcad2MMQwbNizuvoyMjLjtPXr0qPOYaIsXL2bIkCFs37490jZw4EBcLheLFy/mzjvvTDjeRHTp0iVunBs2bKj3uOOOO453332X4447rrVCE2nTvH4/O3eX8W3RbrYWlrC7wkNZpReweP1Byiqrn36YneHm4M4dOSAvO/KUQ1fUzFYREREREXEowSVJEa4/dd9993HsscfG7TNgwICY7czMzFp9fvrTn7Jp0yZee+01Vq5cybJly5g3bx5XXnkljz/+eJNiS6ljeY+1tknjtYa//vWvbNq0iU2bNnH44YfX2r9o0aJWT3CJSONZa9m1p4Jvi3ezaXshu/ZUUF5VBUCVL0B5lZeySi/GWLIz0ul1QD4H5HUgLyuDjBozV0VEREREpDYluKTVfP7555FZUuAUJd+8eTNDhgzhsMMOA6BDhw6Nmq1Un7y8PEaPHs3o0aPx+/2MHTuWJ554gttvv52ePXvSq1evuLOK1q9fD9Re+tceLFq0iOzsbObPn19r37///W9mzpzJmjVrNEtKJMkqqrx8X1zKph272F6yh5JyD0EbxOsPsMdTRVmVl1SXoUO6m8O6d6ZrrpPUcqfq/55FRERERBKh36Cl1Tz88MOMGDEiMiNqwYIFlJSUcNZZZ3HMMcdw+OGH88ADD3DJJZfQsWPHmGN/+OGHRhUw37VrV0yB+NTU1MjMr5KSEnr27MnZZ5/N/fffz4oVKzjttNMA8Pv9zJ07l4yMjGYn2PY2r9fLkiVLOP300znvvPNq7T/99NOZM2cOixYtUoJLJAn8gQA/lJaztbCYLT8UU1RWQZXPRyAIZZVVlFZU4nJBdkYGRxzYlS6hpFaaisOLiIiIiDSZElxt1K5dnyY7hGYrKipi+PDhjBo1ii+//JJHH32Uo446ivHjx+NyuZg/fz7Dhw+nX79+jB8/np49e7Jjxw4+/vhj1q1bx6ZNmxo8x5FHHsmQIUM49thj6datG59//jmPPPIIAwYM4KijjgLg1ltv5fnnn2fkyJFMnjyZgoICXnzxRT788EPmzJlDfn5+a9+KhGzatCnuUxQzMjI477zzeO211ygqKopbVwwgOzubU089leeff57f//73kcL8xcXFcYvC5+bmcu2117bsRYjsh3ZXePh212427Sjih9IySj2VgMXj9VPqqaTS66dDRho9u3aie8ccOmVnKqklIiIiItJClOBqY1JTO5CVdUCywyA1tUOzx1i8eDGzZ8/mrrvuwu/388tf/pIHH3wQt9sNOPWz1qxZw4wZM3jyyScpKSmhW7duDBw4kHvvvbdR57j++ut55ZVXeOCBBygrK6OgoIDLL7+cqVOn4go9WaxLly58+OGH3H777fzxj39kz549HHHEETz99NOMGzeu2dfZ0latWsWqVatqtXfu3JnzzjuPRYsWkZKSwllnnVXnGOeccw5vvPEGb775JmeffTbgJBzvuuuuWn0LCgqU4BJpAmstuysq+aG0jK0/lLB9dylFZR4CwQC+QJA9nir2eKpwp6bQMSuTIwty6ZzTgQ7p7mSHLiIiIiKyzzFtqXD2vmLw4MH2k08+qbfP+vXrOfLII2Pavvvug9YMq0l69Dgp4WOmTZvGPffcw7Zt2zjooINaISqR/VO8nxuydwWDQYrLPfxQWsbmnUUUllaw2+PBHwhgLZRXein1VOEPBsjNTKd7x1wOyMsmLyuDlFDSXUREREREEvfp1u+5dtTPN9vKikPi7dcMrjakKckkERFpXYFgkF17ytmxu4wtO4spKiun1FNFIBggEARPlZeyKi+VPj9Z7lQOyOtAQX4e+dlZpKfp/2ZFRERERPYG/eYtkqDt27fXuz8lJaVRBfJFpO3y+QMU7ilne0kpX/9QQnFZBaWeSiyWQMBS7vVS7vFS5feTlZ5Gxw4ZdO+YS352JjkZ6Rhjkn0JIiIiIiL7FSW4RBJ04IEH1ru/Z8+ebNmyZe8EIyItJpzU+rZoN1sLiyku97DHUwVYfIEg5ZVeyqu8+ANBOqSn0TWvA9075tCxQyYd0t1KaomIiIiIJJESXNLipk2bxrRp05IdRqtZsWJFvfszMzP3UiQi0lxev5/C0nK+K97tzNQq91BW6SS1vP4gZZVVlFd6sViyM9z0yM+le14OeVkZZKlYvIiIiIhIm6EEl0iChg0bluwQRKQZvH4/P5SW813RbrYWllBcXkFZpZfopFZZpRdjLNkZ6fQ6IJ8D8jqQl5VBRlpassMXEREREZE4lOASEZF9XjAY5IfScrYWFrPlh2J2V4RnaoHXH6Cs0kuZpwqXy5Cd4eaw7p3pmusktdyp+r9KEREREZG2Tr+1i4jIPsvr9/N9cSlffF/It0W7KS73AJYqX4DySi9llVWkpBg6pLs57MAuoaRWJu7UlGSHLiIiIiIiCWiTCS5jzCrg5Dp2n2it/aiO4/KAucBIwAW8Clxrrd1Vo985wEzgcOAr4B5r7QtNGUtERNqePZ5Kvtm1m43f/8COkj1UeL0EgrDH46HUU0WKy0lq9enRlc45WUpqiYiIiIi0c20ywQVcBeTWaJsODAL+Xs9xS4A+wOVAEPgdsAw4KdzBGDME+D9gHnAtcCbwnDGm2Fq7PJGxRESk7bDWUrinnM07i/hqxy527SnHFwjg9QfZXeGhospHTqabw7p34YC8bPKyMkhLUVJLRERERGRf0CYTXNbaddHbxhg3MBh4wVrrj3eMMeYEYDhwsrX2/VDbt8DHxphh1tqVoa53Ae9ba68Nbb9rjOkP/AZYnuBYIiKSZD5/gO9LopYhllVgsZRX+dhdXknABuiYlclh3bvQLS9bTz8UEREREdkHtckEVxynA52A5+rpcwawI5yQArDWrjHGbA7tW2mMSQdOwZm5Fe15YL4xJs9au7sxY7XERYmISNNYaykqq2B7SSmbduxi5+4yyiqrCAShzFNJiaeSjNQUuuZ14ODOeXTO6aDZWiIiIiIi+7D2kuC6APgG+KCePn2BDXHa14f2ARwKpMXptx6nzlYfnCWQjRlLRET2st0VHnaU7GHTjl38UFrO7opKAsEAPn+QktAyxOwMN4d260yPTrl07JCJy5hkhy0iIiIiIq2szSe4jDFZwAjgCWutradrJ6AkTnsxcEhUH+L0K66xvzFj1SkYDOLxeOrtY60lGAzGNn69qqGh976eQ5MdQbs1btw4nn32Wbxeb6Tt1FNP5b333uPkk0/mnXfeqXWM2+3moosuYv78+QBs2bKFQw89NO74eXl5FBUVAXDPPfcwffr0OmN56623GDZsWK22xx9/nI8//piioiJyc3MZNGgQo0ePZsyYMVx++eUsXLiwwevs2bMnX331VUIxHHLIIXz99dcAGGPIycmhoKCAY489lksvvZShQ4c2eN6aVq1axc9+9jOeeeYZxowZU2t/OL6vv/6agw46qNb+6667jkceeYRf/OIX/OUvf4l7jpQaM4Cys7MZMGAAV111FRdddFHceMLS0tLo2LEjffr04ZRTTmHChAkUFBQkdI3W2gZ/tuyLyiurQrW1itm5ew8l5R78wQCBIJRXeUMztyx5WRkceWA+B+RWL0P0R/33JyIiIiIi7ZffV//v9m0+wQWcDXSg/uWJSWeMmQBMAPjRj37U9IG8Zc4r2dzZzktaxXvvvcc777zDqaee2qj+5557LiNGjIhpc7tr1xF68MEH6dixY632AQMGRN5ba5k8eTKPPfYY/fv3Z+LEiRx00EGUlJSwYsUKLrvsMr777jsmTJgQk6DZsGEDs2bNYuLEiZxwwgmR9uzs2M9JY2IA6N+/P7fccgsAZWVlfPHFFyxbtoyFCxcyZswYnn766VoJpdbi9/t54YUX6N27N2+99Ra7du2ic+fOcfsOHTqUcePGYa1l+/btPPXUU1xyySVUVlZy2WWX1eofvl/BYJCioiLWrFnDnDlzmDt3Lk8//TTnnntua19eu1Tl87OztIxvdu3m210llFRU4vX7CAahospLWaWXKr+f7HQ33Tvm0C0vm87ZHUjTkxBFRERERPZL7SHBdQHwpbX2kwb6FQNd47R3onqGVvhrXpw+1OjX0FgxrLVPAk8CHHPMMfXNNKuftwzKtjf58BaT3b1NJ7g8Hg/p6em4XK5kh5KwHj164Pf7ueeeexqd4Bo4cGDcWUk1jRw5Mu7spGgPP/wwjz32GFdeeSWPPPJIzD284YYb+Pjjj1m/fj0nnHBCTCJr1apVzJo1ixNOOKHeWBoTA0D37t1rjfO73/2Oa665hv/93//l4IMPZubMmQ2O0xLefPNNfvjhB1588UVOO+00XnjhBa666qq4fQ855JCYuMeOHcthhx3G3Llz4ya44t2vr776ijPOOIOLL76YI444olbyb3+2p6KSr3YW8dXOXZSUefCE/pXG4/Wzx1OFx+cnKy2VTtmZHNgxh07ZWSoaLyIiIiIibTvBZYzJwynqPrsR3TcAJ8Vp7wssC73fBPhCbe/V6BMENiYwVp1cLheZmZn19jHG1E7OGFf1q/vRDZ2m9Wz/V3UcTUggTZs2jXvuuYdPP/2UOXPm8PLLLxMIBDjrrLN48MEHOeCAAyJ9165dy7Rp0/jggw+orKykf//+3HnnnYwcOTLSZ8GCBYwbN44VK1bw+uuv8/zzz7N9+3aKiorIyclh9uzZPPPMM2zduhW3203v3r2ZMGECkyZNioyxbds2br/9dt566y327NnDEUccwfXXX8/YsWMjfbZs2ULv3r2ZMWMGP/rRj7jvvvvYvHkzffr04fe//z2nnXZaQvfBhOr+1Pw+Z2ZmctVVV3HjjTeycuVKhg8fXuu48DHhr3E/L3Wcq75+lZWV3HvvvRx++OE8/PDDpKbW/hFQM7EVFh1TvHM0NoZ4Y4a53W7mzZvH+++/z0MPPcRtt91Gbm5uQmM1Jb5nP0VEEQAAIABJREFUn32WH//4x5x88smcfvrpLF68mGuuuSbueWp+L7p160bfvn35z3/+E9NeXzyHHXYY8+fP56STTmLOnDksWrSoUddojGnwZ0t7tcdTyaYdu/j8ux/YubuMQDBAlS9AqcdHRZUXd2oqeTnZ9O2US+ecLHIy0iPfUxERERER2felptX/D9ttOsEFjALSadzyxDeAu4wxQ6y1qwGMMYNxama9AWCtrTLGvAv8Cngi6thfAx+FnqDYqLGkYWPGjKFz587MmDGDL774gnnz5rF+/XrWrFmD2+3mgw8+YPjw4fTr14+pU6eSkZHBkiVLGDVqFH/605+48MILY8abMmUKOTk53HrrrVRUVOB2u5k+fTrTp09n/Pjx3HjjjXg8HtatW8fq1asjCa7CwkJOPPFEdu3axeTJkykoKGDJkiWMGzeOwsJCbrrpppjzLF26lMLCQiZOnEhmZiZz585l1KhRbN26lfz8/Ba5N5MmTeL+++/n7rvvrpXgiqeiooLCwsKYtuzsbDIyMmLaiouLa7UBdOnSBYDVq1dTWFjINddcQ1paWjOuoG4NxdCQ1NRULrroIn7zm9+wevVqzjzzzITOX1ZWVutegXMP49m9ezcvv/wy06ZNA2D06NFceOGFfPHFFxx++OENns/v9/PNN98k/NkYMmQIhxxyCMuXL0/ouH1NWWUVX+3YxYZvd7KztAx/IEBZpZficg8uAzmZGfTq2okuudnkZqaT0g5nbYqIiIiISOtr6wmuC4B/W2vX19xhjFkFYK0dGvr6kTFmObDQGHMTzoys3wGrrbUrow6dAawyxszFmY11Zuh1erhDAmNJPfLz81m+fHmkjtKAAQOYMGEC8+fP5/+zd+/RkV2Fne+/u6pUpWdJJalKj+52v9zddtvGBmychCbAjIcEWIRnIMMNN8aXGBISCLkXAgHuNeMQBnK5kxkgQNaEMNgeWEnAHnAIGIOxY8NgN3612/1wd+utKlVJpXqfqnNO1bl/SN3TbvdbUp+S9PusVUutc/Y59ZO8lrzqt/be59Zbb+XWW2/lhhtu4IEHHjgx5v3vfz+veMUr+MhHPsLv/M7vPG+GRiQS4aGHHnpeMfPd736X173udfzd3/3dGXP8x//4H5mcnOQHP/gBv/EbvwEsFEyvfOUr+eQnP8m73/3u5+23dOTIEQ4fPszAwACwsOfSi1/8Yr75zW/y/ve/f1l+N21tbXz0ox/lgx/8IN///vfPWeJ85jOf4TOf+czzjn35y1/mfe973/OOvehFLzrt9Y7jEAqFePbZZ886bjmcK8P5OL5k78iRIxf8/n/wB3/wvNl75/JP//RP1Gq1E4Xqb/3Wb9HZ2ckdd9xx2k3za7Uas7OzeJ5HMpnkr/7qr0ilUnzwgx+84KxXX3013/3udykUCuc9U22tKB8vtqYzzOSLuPU6lZrDXLFCOBRgU183G3q7iXW0EbpEe7GJiIiIiMjq1bQFlzGmH/i3wCfPMKQdGD3l2DuA/wR8DQgA9wIfOHmA53kPG2PeBvwF8AfACPBOz/NOnUZxznvJ2f3xH//x8zYJv/nmm/nwhz/Mvffey4033sjBgwf5kz/5E+bnn7+t2ete9zo+/vGPc/jwYXbt2nXi+O///u+/YNZRT08P+/fv58CBA1x55ZWnzXHvvfdy9dVXnyi3YOGJdh/60Id4+9vfzo9//GPe/va3nzj31re+9US5BXDdddcRjUY5duzYxf0izuC9730vn/vc57jtttvOWXDdfPPNL3hK3+l+3m9+85unnSl1/L9DoVAAWNEy5VwZzkdXVxcAxWLxgt//ox/96PM2xz/uG9/4xmmXAt5xxx3s2bPnxMMh2tvbedOb3sSdd97Jpz71qRcsg7vzzju58847T3wfCAR473vfy2c/+9kLznryz7leCq5KzT4xY2smX8Sp17Fsl2ypTDAQYENvlM3xGLHOdgJagigiIiIiIuepaQsuz/NmgdOuoTLGRIBrgQ+fck0OePfi62z3vodz7KV1vveSMzu5nIKFUmnbtm2MjIxw+PDCdmfve9/7XjAL6bh0Ov28e2zfvv0FY/7iL/6CN77xjezevZudO3dy00038du//du86lWvOjFmdHT0BU8gBNi9ezcAIyMjzzu+efPmF4yNxWJks9kz/KQXJxKJ8LGPfYw/+qM/4nvf+x5veMMbzjh2+/bt3HTTTee85549e866wfvxEuViiqPzda4M5+N4vuMF0IW46qqrTvu7evjhh19wbGxsjIceeohPfOITz5sttmfPHu68804eeeQR9uzZ87xrXvva1/Knf/qnuK7LU089xac//WlyudxFLflcys+52li2w8jMHAen06Tmi9h190SxFTCGoZ4om/p76OvqULElIiIiIiIXrGkLrnO4Htjned6D5xwpTanRaADwl3/5l9xwww2nHXPqk+VOt7n2y1/+co4ePco///M/c//993PPPffwN3/zN7z3ve/lK1/5ykVlO9NMI8+7+Idjnsnv//7v89nPfpbbbrvtrAXXcjk+6+vpp59+3kb+zeaZZ54BFjZjX0l33XUXnudx++23c/vtt7/g/PHZXScbHh4+UaD95m/+Jjt27OCtb30rv/Zrv8YHPnBhkzyfeeYZEonEmp69VW80GMvM8/TYNNPzBWz3eLFVwRgY6Olic39MxZaIiIiIiCzJqiy4PM97hIWSS5rYoUOHTsySgoU9mEZGRtizZ8+J4qKjo+O8ZiadTXd3N+985zt55zvfieu63HzzzXz1q1/lYx/7GJs3b2bLli0cPHjwBdcdOLCwtdvWrVuX9P5LEQ6H+fjHP8773vc+7r777hV/vz179tDb28tdd93Fn//5n5/3nliXkuu63HXXXXR0dLygXFpud9xxBzfeeOMLHjQA8N//+3/nH/7hH/gv/+W/EIlEzniPt7zlLbz85S/n9ttv55ZbbqGzs/O83vvhhx/m2LFjvOtd77ro/M1utlBm33iSozNzlKpVak6duWIF8IhHO9gS76Wvq10bx4uIiIiIyJLpU4WsmC984QvU6/UT33/9618nl8vx+te/npe85CXs2LGDz3/+8+RyuRdcm8lkzus95ubmnvd9KBQ6MfPr+H3f8IY3sG/fPn70ox+dGOe6Ln/9139Na2vrkgu2pbrlllvYsmXLiaf4raS2trYT+5v9yZ/8yYmZdCd77LHH+PrXv77iWU7HdV3e//73c+jQIT74wQ+u6MymvXv3cvDgQd71rnfxtre97QWvP/zDPySXy3Hvvfee814f/ehHmZ2dPe9ZgyMjI7z73e8mEonwkY98ZKk/StOxbIenRqf40dOHeHpsmnzFIpMvkymU6Y+289LtG3npto0kujtVbomIiIiIyLJovukbsmZks1le85rX8OY3v5kjR47wpS99iWuuuYZbbrmFQCDA3//93/Oa17yG3bt3c8stt7B582ZmZmb4xS9+wbPPPsvRo0fP+R5XXnkle/bs4YYbbmBgYIBDhw7xxS9+kauvvpprrrkGgD/7sz/jW9/6Fm9605v44z/+YzZs2MA//uM/8sgjj/BXf/VX9Pb2rvSv4qxaWlr4xCc+wXve854l3+vuu+8mFou94PjLXvYydu7cCcCHPvQhDh06xJe+9CUefPBB3v72t7Nx40bm5+f5yU9+wve//30+/elPr2gGgFQqdWKz9nK5zOHDh/nOd77D6Ogov/u7v3vaJxgup+Mbzp9ufzaAV77ylXR3d3PHHXfw1re+9az3ev3rX89VV13F5z//ef7oj/6I1tbWE+d+9rOfAQvLcrPZLI8++ih33303oVCIu+666wVLcVezRqPBxFyOp8eSTMzmsOsuBcsmV67Q09HG7k0DDPZ0qdQSEREREZFlp4KrWaWe9DvBkt1555187nOf45Of/CSu6/KWt7yF//yf/zPhcBhY2D/r0Ucf5fbbb+dv//ZvyeVyDAwMcO211553wfKhD32I733ve3z+85+nVCqxYcMG3vOe9/Dxj3+cwOKH6P7+fh555BE+9rGP8V//63+lWCyya9cuvva1r/HudzfHMwR+7/d+j8985jPnVeqdzZn2gPrCF75wolwyxvDVr36VN77xjXzlK1/hi1/8Itlslmg0yvXXX88dd9zBv//3/35FMwDs37+fd73rXRhj6OzsZMOGDbzyla/ka1/7Gq9+9asv+v3Ph+u6fOtb3+K6665j06ZNpx3T0tLCa1/7Wr797W8zNzdHX1/fGe9njOHDH/4wN998M1/72tf4wz/8wxPnvvzlL/PlL3+ZUChEd3c3u3bt4sMf/jC33nrrkjfjbybzpQr7J2d4bjpD3rKw3TqZQomWYJAdQ/1siffSFr7wjfhFRERERETOh1mJjbPXu+uvv97bu3fvWcccOHDgxIbfJ4z+FOzSwstv4c6F15ZXXfClt912G5/61KeYmJhYUx/gRfx22r8bPrNdl+eSs+yfSJHKFXHqDebLFSzbYaC7k+0DffR2tmO0gbyIiIiIiCzBvvEkH3jzb4x41cq2053XDK5mc7xYEhFpYp7nMT1fYN94ktF0lqrjULJssqUK0fYIL7pskA293YTO8FRSERERERGR5aSCq5lcxGwpufRSqdRZzweDQeLx+CVKs/bl83ksyzrrmN7e3hNLX2Xl5coWB6ZmeC45S7ZUxnEbZAplAgHYNtDHlkSMztYzP3lSRERERERkuangErlAQ0NDZz2/efNmRkdHL02YdeCDH/wg/+2//bezjnnggQd41atedWkCrWNV2+G5ZIYDU2lSuSJuvUGuYlGu2sSjHWwb6CMe7dByRBERERERueRUcMmyu+2227jtttv8jrFifvSjH531fFtb2yVKsj585CMf4Xd/93fPOubaa6+9RGnWp3qjwcRsjn3jSSbmctiuS6m6sByxszXM7k0DbOrrIRzSckQREREREfGHCi6RC3TTTTf5HWFd2b17N7t37/Y7xrqVzhfZPzHDsfQcRau6+HTEMqGAYUsixpZ4L9G2Vr9jioiIiIjIOqeCS0REXqBUrXFgcobDyQyZQpl6o0G2VKHquAx0d7I10Ut/l5YjioiIiIhIc1DBJSIiJzhunWMzczwzkSKZK+C4dQpWjVzZoqejlV3DcYZjUT0dUUREREREmooKLh95nqfZDyJyXjzPW/H3mM7meXo8yVhmHsu2sWyX2WKZtpYQu4bjbI7HaAu3rHgOERERERGRC6WCyyctLS1YlkV7e7vfUURkFbAsi5aWlSmXao7Ls5Mz7J9IMVss4dQbzBXLNBoeG3ujbEn0EevQwxNERERERKR5qeDySSKRYGpqig0bNtDW1qaZXCJyWp7nYVkWU1NTDAwMLPv9M4UST4xMcnQmS81xyJUtClaN/q4Otg30Eo92EgwElv19RURERERElpMKLp9Eo1EApqencRzH5zQi0sxaWloYGBg48XdjObj1OoenMzw9niSVK+LU66TzJSKhILs3DnBZfw/hkP4XISIiIiIiq4M+vfgoGo0u6wdWEZHzkStbPDk6xeHpDBXbpmDZ5MoWiWgnO4b66Ovq8DuiiIiIiIjIBVHBJSKyTjQaDUbSWZ4YmWJ6voBTr5MplDAGdg71szXRS6RF/1sQEREREZHVR59kRETWgVK1xtNj0xycylCwLMo1h7limd7OdnYM9ZOIdmovQBERERERWbVUcImIrGGe5zExl+OJkWnGZ+dx3DpzxTJOvc62RB/bB/toC6/M0xlFREREREQuFRVcIiJrlGU7PDOe5MBUmmypTNV2yRTLRNsi7N40wFAsSkCztkREREREZA1QwSUissZ4nsdUNs9To9OMZeapuS7zJYuybbOxN8rlg3G62iJ+xxQREREREVk2KrhERNaQU2dt2W6ddL5Ee6SFazYNsqm/h2Ag4HdMERERERGRZaWCS0RkDTg+a+vJ0WnGMllst8582aJctRmKdbF9sJ9YR5vfMUVERERERFaECi4RkVWuUrPZP5E6MWur5tTJFBZmbe3eNMBl/T20BIN+xxQREREREVkxKrhERFYpz/OYnMvz1NjpZ21dPthPj2ZtiYiIiIjIOqCCS0RkFarUbJ6ZSHHwpFlb6UKJDs3aEhERERGRdUgFl4jIKnJ81taTo1OMz85r1paIiIiIiAgquFaE45Rx3SqhUKvfUURkDXHcOvsmkjwznnrBrK2rLxtgU18PIc3aEhERERGRdUgF1wpw3QrPPfctNm36t3R2bvI7joisAYVKlcdHJjk0ncGybbIlzdoSERERERE5TgXXCvC8BrZdYHT0XhKJG4jHX4oxxu9YIrJKTc7l+OWxScZnc9iOSypfpLUlpFlbIiIiIiIii1RwrZBSaZL29gFmZh6lXE6yceNNtLRohoWInD+3XufgVJqnxqbJFEpYtksmX6I/2sHO4Tj9XR1+RxQREREREWkKKrhWQDAYJhiMUKkkiUR6ADh27B/ZuPHf0dEx5HM6EVkNytUaT4xOc2ByhnKtRq5cpVStsTkeY8dQP+2RsN8RRUREREREmoYKrhVhaG8fxPNcSqUJXLdGo5FgdPS7DAz8Cn19L9KSRRE5o5lckb1HJxjJZKk5dTKFIsGA4YoNCbYmegkGAn5HFBERERERaSoquFaIMYbe3hfR2tpPNvs05fIU7e1xkslHqFSSbNjwaoLBiN8xRaSJNBoNnkvO8sToFKlckZrjki6U6GlvZedwnES0U+W4iIiIiIjIaajgWmFdXZcRifSQTu+lXE4SifSSzx+jWp1j48Z/R3t7wu+IItIEqrbDU6PT7J+coWBZFCybfNliuDfKruE4na0qxEVERERERM5EBdclEA5HGRr6debmnqRcnqJer+J5dUZG7mZoaA+9vVf5HVFEfJQtVdh7dJwjyTmqjstssUzDa7BrOM7WgV5a9JREERERERGRs9JGLpdIMBgikbievr5rqderlMtTOE6FqakHmZz8CY1Gw++IIuKDuWKZRw6OcGAyTblmMzWfJxwK8KLNw+wY6le5JSIiIiIich40g+sSi0a3EA73kMnspVyeprW1l/n5gzhOicsuey3BYIvfEUXkEsmWKvz88BjHZuawbId0ocxgTye7huN0t7f5HU9ERERERGTV0AwuH7S29jA8/Ou0tQ1Qrc5Rrc5RKk0yMnI3jlP2O56IXALZUoWfHRrlaGr2RLm1ub+HazcPq9wSERERERG5QCq4fBIMhhkYeBnR6DZsO49lzWBZGY4e/Q7VatbveCKygs5Ubl25MUGkRRNrRURERERELpQKLh8ZY+jru4ZYbDeOU6ZcTmLbOUZG/gflctLveCKyAuZPKreqjvu8ciscUrklIiIiIiJyMVRwNYGenh3E4y+h0bCpVJLYdpHR0XspFEb8jiYiy+jUcmsmX1K5JSIiIiIisgxUcDWJzs5NDAzciOc1KJencd0y4+M/JJvd73c0EVkGx8utIyeVW5ep3BIREREREVkWKriaSFtbgsHBlxMIBCmVpnGcMlNTDzIz86jf0URkCXJl6wXl1qa+bq7coHJLRERERERkOajgajKRSA9DQ6+gpaWdSiWF45RIp/cyOfkAjUbD73gicoFyZYtHTlNu7d44oA3lRURERERElokKribU0tLB0NAeIpEeLCuNbeeZnz/A+Pj3qdcdv+OJyHnKlS1+dvj5e26p3BIREREREVl+KriaVDAYYXDw12hvH6RanaNazVIsjjM6+j9wXcvveCJyDvnKQrl1JDmLZTukCyq3REREREREVooKriYWCIRIJF5GZ+dmbDuHZaWpVNIcO3YPtl30O56InEGlZvPzQ2McSc5SdRxm8kU29EZVbomIiIiIiKwQFVxNzhhDPH4dsdgVOE6JcjlJtTrHsWN3U63O+x1PRE5RbzR4anSaozMLyxJTuSIbNXNLRERERERkRangWiV6enbR1/ci6nWLSiWJbecZGbmHSiXtdzQROcnh6Qz7J2eoOXXS+SLDsYWZW60tLX5HExERERERWbNUcK0i0ehW4vGX0mg4iyVXidHR71IqTfgdTUSAVK7AU6PTlKpVMsUSXW0Rdg7HVW6JiIiIiIisMBVcq0xn50YSiRtpNBpUKlM4Tpmxse9TKIz4HU1kXStVa/zy6CSpfIGCVQPPY+dQnGhbq9/RRERERERE1rymLLiMMSFjzEeNMc8ZY2rGmEljzH86j+u6jTF/b4yZN8bkjTF3GWP6TjPujcaYfcaYqjHmWWPMOy72Xn5ob08wOPirgKFcnsZ1K4yP/4Bs9qDf0UTWJbde54mRKY6ls9ScOvlKla2JPgZ7uvyOJiIiIiIisi40ZcEFfB34APD/Aq8BPgpY53HdPwCvAt4D3AzcANxz8gBjzB7g28ADwGuBfwa+aYx5zYXey0+trb0MDb2cQCBMqZTEdStMTf2ETOYJv6OJrDsHp9IcnEpju3XShRIbeqNsHejFGON3NBERERERkXWh6R7pZYz5TeAdwLWe5z17Adf9Kgtl2Cs9z3to8dgU8AtjzE2e592/OPSTwEOe531g8fsHjDFXAf83cN8F3stX4XA3Q0MvJ5X6OeVyira2AVKpn1OvVxdneInISpvK5nlqbJpyrUamUKSnvY2dQ3FagkG/o4mIiIiIiKwbzTiD6xbgJxdSbi16LTBzvJAC8DzvUWBk8RzGmAjwahZmZ53sW8CvGmO6z/dezaKlpYOhoVcQDkexrBSOUyKTeYKpqZ/SaDT8jieyphUqVfYenSRTKJErVwkYw87hfjpbI35HExERERERWVeaseC6EThsjPmiMaZgjKkYY75jjBk+x3VXAKfbhOrA4jmA7UDLacYdYOF3sfMC7tU0QqEIQ0O/RmtrH5aVxrbzZLPPMjl5H41G3e94ImuS49Z5fGSS8dl5qrZLqVpj20AfiWin39FERERERETWnaZboggMsrDn1VPA7wBdwOeAu40xv+J5nneG62JA7jTH54FtJ43hNOPmTzl/Pvc6I8/zqNVcqlWbQODSzaLq7n4pjvMEhcIMkbBNreZSLpfYtOk1BIMtlyyHyFrneR77xpLsH53CqtVIZQtc1t/DcLQdx7b9jiciIiIiIrLmuM7ZP2s1Y8FlFl9v9DxvDsAYkwQeBP4N8GMfs52RMeZW4FaA4eG4LxkCgSD9/S8hm91HuTyJ5y3M3hob+x6XXfZaQqE2X3KJrDWTczmenUxTdWzS+TK9XW1sH+gjpH23REREREREfNGMSxTngX3Hy61FDwM2sPsc13Wf5niM/zVD6/jXU8fFTjl/Pvd6Hs/z/tbzvOs9z7s+Fus6S8yVFQgE6O+/lmh0G7ZTolrNYFmzjI5+j1qt4FsukbUiX7Z4cnSabLnEfKlKOBjg8sF+2iJhv6OJiIiIiIisW804g+sA0Hqa4wY423q/g8ArTnP8CuCexX8fBZzFYw+eMqYBHL6Ae52RMYZIJERra5hAwJ9f8dDQtbS1tTE/fwDXnSUcDpJK/YDNm19PW1u/L5lEVjvbddmfnCBVtLC9ANUGXLVpkOH+Pr+jiYiIiIiIrGmhlrNPKmjGGVz3AtcYY05uYX6dhc3hnzrLdf8CDBpj9hw/YIy5noU9s/4FwPO8GvAA8NunXPsO4Oee5+XP916rQU/PTvr7r6Ner1KpJKnVCoyM3EOpNOV3NJFVx/M89o2nOJycxXZdMoUSl8W7uaw/du6LRUREREREZEU1Y8H1t8Ac8D1jzBuMMe8E7gDu9zzv4eODjDE/Ncb89Pj3nuf9HLgP+IYx5i3GmDcBdwEPe553/0n3vx14lTHmr40xrzLGfA54HfAfLuJeTa+razOJxMtoNBwqlSkcp8zY2L0UCiN+RxNZVUbSWZ4ZT1K1HWbyReLRDnYMxgkGmvHPqIiIiIiIyPrSdJ/MPM8rsLCZ/DzwLeBLLGws//ZThrYD6VOOvYOFpYdfA74B/BJ48yn3fxh4G3AT8EPgt4B3ep5334Xea7Xo6BhkYODlgKFcnsZ1K4yP/4Bs9lm/o4msCplCiV8em2S+XCFbqtAWbmHXcIK2sJ5OKiIiIiIi0gyacQ8uPM87wsKsqtMyxkSAa4EPn3JdDnj34uts97+Hc+yldb73Wi3a2noZGno5qdQvKJWStLcPMDX1U1y3QiJxvd/xRJpWpWaz9+gEU9k8Jcum5rpctXGQ3s52v6OJiIiIiIjIoqabwXWermfhSYsPnnOknBAOdzM0tIeWlnYqlRSOU2Zm5lGSyYfxPM/veCJNp95o8MTIFEdn5rDdOvMViy3xXjb19/gdTURERERERE6yKgsuz/Me8TxP044uQktLO4ODewiHu7GsGRynwOzs00xO3k+jcbaHVIqsPwcmZ3h2coaaU2cmV2Sop4vLB/sIGON3NBERERERETnJqiy4ZGlCoQhDQ79Ga2scy5qlVpsnl3uOiYkfqOQSWTQxm+OpsWnKtRqZQpGejlZ2DScIh5pyZbeIiIiIiMi6poJrnQoEWhgY+BU6OjZQq81Trc5RKIwyNfVjLVeUdS9XtvjlsQkyhRK5skUwYNg5HKerLeJ3NBERERERETkNTUVYxwKBAPH4SzEmSKk0jjGGXO45gsE2hof3+B1PxBc1x2Xv0QnGZ3NYtkuxarN74wAD3V1+RxMREREREZEzUMG1zhlj6O+/Ds9zKZenMSbI3NzThEIREokb/I4nckk1Gg2eGpvmcDKD7bpkCiW2JGJsicf8jiYiIiIiIiJnoYJLFkuul9JoOFhWBmOCzMw8RjDYRl/f1X7HE7lknkvOsn88Rc1xSeVKJKJd7BiMEwxoNbeIiIiIiEgz06c2ARaWKyYSNxCJxLCsNI5TIZn8V3K55/yOJnJJpHIFnhidIm9ZzBbKdLS2sGtDnLZwi9/RRERERERE5BxUcMkJxzeeb2npwrJmcN0Kk5M/oVgc9zuayIoqVWvsPTpJKlegYNnUvQY7h+LEOtr8jiYiIiJCG8aeAAAgAElEQVQiIiLnQQWXPE8wGGZw8FcJhdool2eo1ytMTPyQcjnpdzSRFeG4dX55bJKRdJaaUydfttiW6GM4FvU7moiIiIiIiJwnFVzyAqFQGwMDv0Iw2EK5nMJxKoyN/QvV6pzf0USWled57J9IcXAqje26zOSLbOyLsnWgF2OM3/FERERERETkPKngktMKh7sYGLgRMFQqSRynzOjovdRqeb+jiSybkXSWp8eTWLbNTK5Eb2c7O4bitASDfkcTERERERGRC6CCS84oEokxMHAjntfAspLYdoHR0XtxXcvvaCJLlpwvsPfoBNlSmWzJItwSYNdwnM7WiN/RRERERERE5AKp4JKzamvrJx6/nkbDoVJJUavNL5ZcNb+jiVy0bKnCo0fGmZ7PU7RsqrbD5QP9xKOdfkcTERERERGRi6CCS86po2OI3t7rqNdrVCozWFaG8fHv02jU/Y4mcsFK1Rq/eG6M0XQWy3bJlS22D/RzWTzmdzQRERERERG5SCq45LxEo5cRi11FvW5hWWnK5SSTkz/G8zy/o4mct5rjsvfoBEdSc9Rcl0yhzOZED9sHewloU3kREREREZFVK+R3AFk9enoup9Gokc8fwZgQcIRwOMrg4K/4HU3knNx6nSdGpnh2cgbbcUnligzHouwaShDSpvIiIiIiIiKrmgouuSC9vVfhuhbl8hSBQIhM5nFaWjrp67va72giZ+R5Hs+Mp9g3nqRquyRzBeLRDq7cOECkRX8GRUREREREVjt9spML1t//Yly3SrU6izEtJJMP09LSRTS62e9oIqd1aDrNE6NTlGs1ZvJFou0RrtwwQEck7Hc0ERERERERWQbag0suWCAQZGDgBlpaOrGsFPW6xeTkfVhWxu9oIi8wPjvP4yNT5CsWmUKZcCjIlRsG6Olo8zuaiIiIiIiILBMVXHJRgsEIAwM3Egi0UC7P4DgWY2Pfx3FKfkcTOSGdL/Loc+Ok80Vy5SqNRoNdw3Hi0U6/o4mIiIiIiMgyUsElF62lpZOBgRuBBpaVwrYLjI7+M/W67Xc0EfIVi188N85kNk+palOu2Wwf7GdDb7ff0URERERERGSZqeCSJWlt7SUefyn1uk2lkqZanWN8/Ac0Gg2/o8k6VqnZ/OK5MUbSWaq2w3zJYmuil62JXowxfscTERERERGRZaaCS5aso2OY3t6rqdctLCtDqTTJ9PSDfseSdcp2XfYeneBwcpaa45IulLisv4cdQ/0EA/qTJyIiIiIishbpKYqyLLq7t+M4ZYrFEQKBEPPzBxaXMN7gdzRZRxqNBk+OTvPs5Aw1xyWVLzIU62LncJyWYNDveCIiIiIiIrJCVHDJsunru4Z63aJSSREItJBOP0Y4HCUW2+V3NFknDkyl2TeexLIdUrkSsY42rtwwQFu4xe9oIiIiIiIisoK0XkeWjTGGePwlRCIxLCuD61pMT/+UUmnS72iyDoxlsjw5OkXRqpIulOiIhNi9cYDO1ojf0URERERERGSFqeCSZRUItJBIvIxQqI1KZQbXtRgf/yG1Ws7vaLKGZQolHjsyQaZQYr5kYYBdwwl6O9v9jiYiIiIiIiKXgAouWXahUCsDA79CIBCkUknhOBUmJn5Eve76HU3WoKJV5dHnxpnM5ilVbSq2w+WD/Qz2dPkdTURERERERC4RFVyyIsLhLhKJ62k06lhWGsvKkEr9zO9YssbUHJfHjkxwLJ2l5rjMlyy2JnrZHI9hjPE7noiIiIiIiFwiKrhkxbS1JYjFrqBet6jV5slmnyGXO+J3LFkj6o0GT4xMcXA6Tc1xmMkV2dgX5fLBfoIB/WkTERERERFZT/QpUFZUd/cO2tri1Grz1OsWyeSD2Hbe71iyynmex4HJGZ6ZSFK1XVK5EvHuDnYNJwiHgn7HExERERERkUtMBZesKGMM/f0vIRiMUKlkFvfjup9Go+53NFnFRjNZHh+ZolStkS6U6GoLc+WGAdojYb+jiYiIiIiIiA9UcMmKC4Va6e9/CZ5Xx7IyVCozzMz8T79jySo1kyuy9+gE2VKZbMkiGDDsGk7Q09HmdzQRERERERHxiQouuSTa2xN0d+/AdSvUajlmZ5+iUBjxO5asMvmKxaNHxpnKFihZNlXHYYeemCgiIiIiIrLuqeCSSyYW20Vrax+1WpZ6vcrU1APYdsnvWLJKVG2Hx45MMJLOUrUd5isW2xJ9XBaP+R1NREREREREfKaCSy4ZYwL097+UQCCMZaVxnDKTkz/C8xp+R5Mm59brPD4yyeHpDDXXJV0ocVlfD9sH+wgY43c8ERERERER8ZkKLrmkWlra6O9/MY2GS7U6S7mcZGbmMb9jSRPzPI/9Eyn2T8xQdVxmckUGurvYORynJagnJoqIiIiIiIgKLvFBR8cg0eh2HKeMbeeZnX2cYnHC71jSpI7OzPHk6DTlWo2ZfJFoe4QrNiRoC7f4HU1ERERERESahAou8UUsdiXhcIxqdWE/rsnJH+M4Fb9jSZOZnMux98gE8+UKc8UKLaEAVwwP0N3e6nc0ERERERERaSIquMQXgUCQROKlBAIhKpUZHKe0uB+X53c0aRKzhTKPHhknlS9QsGrYbp0dg3ES3Z1+RxMREREREZEmo4JLfNPS0kFf37Un9uMqlabIZPb6HUuaQNGq8ujRccZnc1RqDvlKlcuH+rmsv8fvaCIiIiIiItKEVHCJrzo7NxCNbsVxSjhOgXR6L6XStN+xxEc1x+WxIxMcTc1huy6zxQpb471sS/Ri9MREEREREREROQ0VXOK7WGw34XA3ljVHvV5jYuI+HKfsdyzxgVuv8/ixSQ5Op6k5Dqn5Ihv7ouwc7icY0J8rEREREREROT19YhTfBQIh4vHn78c1Pv5DGo2639HkEvI8j2fGU+wbT1K1XVK5IonuLq4YThAOhfyOJyIiIiIiIk1MBZc0hXC4i/7+a2k0HCwrTaWSIpV6xO9Ycgkdns7w5NgUFdtmJl8k2h7hyo1x2iNhv6OJiIiIiIhIk1PBJU2jo2MD3d07cN0KtVqOublnmJ8/4HcsuQQmZnM8PjJJrmyRKZQJh4JcuWGA7vY2v6OJiIiIiIjIKqCCS5pKLHYlbW0JarUsjmMxPf2vVCppv2PJCsoUSjx6ZJyZfJF8uUqj0WDXcJx4tNPvaCIiIiIiIrJKqOCSpmKMIR5/CaFQO5Y1g+taTEz8EMex/I4mK6BQqfLoc+NMzOUo1xyKVZvtg/1s6O32O5qIiIiIiIisIiq4pOkEgxESiRswBiwrjW0XmJz8EZ7n+R1NllHVdnjs6DjH0llqjku2VGHbQIytiV6MMX7HExERERERkVVEBZc0pUikh76+66jXa1hWhlJpklTq537HkmXi1us8PjLJoakMNcchnS+xsbebywfjBAP6syQiIiIiIiIXRp8kpWl1dW0iGt2K45Sw7Tyzs0+Syx3xO5Ysg4NTaZ4ZT2E5LqlckUR3J1dsSBAOBf2OJiIiIiIiIquQCi5parHYVbS29lGtzlGvW0xNPUC1Out3LFmC5HyBp8eTVGybdL5Id3srV2xI0BZu8TuaiIiIiIiIrFIquKSpBQJB4vHrCQZbqVTSuK7F+Ph91Ou239HkIlRqNo8fmySdL5Kv1AgGDDuH43S3t/odTURERERERFYxFVzS9EKhVuLx6wEPy5qhVptnYuJ+bTq/yjQaDZ4eSzKSyWK7dQpWla2JPhLRTr+jiYiIiIiIyCrXlAWXMeZmY4x3mtf7znFdtzHm740x88aYvDHmLmNM32nGvdEYs88YUzXGPGuMecfF3ksujba2PmKxq6nXa1SrsxSLo2Qyj/kdSy7AsXSWZydnsJ066XyJoZ4utiRiemKiiIiIiIiILFnI7wDn8G8A66Tvj51j/D8AO4H3AA3gs8A9wCuODzDG7AG+DfwN8AHgdcA3jTHznufddyH3kkuru3srtp2jVBonGIwwM7OX1tYE0egWv6PJOcwVyzwxMknBspgrlulsDbNzOE5LUJvKi4iIiIiIyNI1e8H1mOd5pfMZaIz5VeA1wCs9z3to8dgU8AtjzE2e592/OPSTwEOe531g8fsHjDFXAf83cN8F3ksusb6+a7DtApY1RyAQYWrqJ7S2/jbhcJff0eQMao7L4yNTTGcLlKo2bqPO7qEBom3ad0tERERERESWR1MuUbxIrwVmjhdSAJ7nPQqMLJ7DGBMBXs3C7KyTfQv4VWNM9/neS/wRCIRIJG4gEGjBsmZwnDKTkz/WflxNyvM89k+mOJKaxa7XyZYsNsdjDMWifkcTERERERGRNaTZC66jxhjXGHPIGPPec4y9Ajh4muMHFs8BbAdaTjPuAAu/i50XcC/xSUtLO/H4i2k0XKrVWcrlaTKZX/odS05jYi7HM+MpqrZDOl8iEe1k20AfAe27JSIiIiIiIsuoWZcoJllYSvgoEAR+B/iKMabd87z/dIZrYkDuNMfngW0njeE04+ZPOX8+9zojz/Oo1VyqVZtAoHGu4XIRAoFeIpFNFItj1OsRHOd/EgzGaW9P+B1NFhUrVR49eIzM/DzzpSphPLb2dxFoNLBrNb/jiYiIiIiIyCriOvZZzzflDC7P837oed5feJ53n+d5/+J53u+xsKzwE8aYpsxsjLnVGLPXGLN3fr7od5x1oafnCsItnVSrc7iuzdTUT6nXHb9jCeDW6zw1nmQim8eyXcq2zZZEjFhHu9/RREREREREZA1qyrLoDP4J6AW2nOH8PNB9muMx/tcMreNfTx0XO+X8+dzreTzP+1vP8673PO/6WEwbnl8KgUCIvr6XYIyhWs1g23lSqZ/5HUuA55KzHEnO4rgus4Uym3q72djX43csERERERERWaOadYni6XinfD3VQeAVpzl+BXDP4r+PAs7isQdPGdMADl/Avc7IGEMkEqK1NUwgsJp+xatPa2sfHleTzT6D5xWwrGPUatvp6dnhd7R1K5UrcGgmS83zyFo2fT3d7LpsmLZI2O9oIiIiIiIiskqFWs7+mXI1zeB6GzALjJ3h/L8Ag8aYPccPGGOuZ2HPrH8B8DyvBjwA/PYp174D+LnnefnzvZc0j2h0G21tA9h2Dte1SCYfwra1TNQPlZrN4yNTzORLFKwaAWPYMdRPh8otERERERERWUFNOb3IGPNtFjaYf5qFTebfsfj6gOd5jcUxPwXwPO9Vi19/boy5D/iGMeb/YmFG1meBhz3Pu/+k298O/NQY89cszMZ63eLrN48PuIB7SRMwxtDffx3T0w9iWRmCwTCTk/ezdeubMHpa3yXTaDTYN5ZkZGYO23XJl6vsGo4z0N3pdzQRERERERFZ45p1Btch4Bbg28A/AruB/93zvC+cNKYdSJ9y3TtYWHr4NeAbwC+BN588wPO8h1mYDXYT8EPgt4B3ep5334XeS5pHKNRKf/+1eJ5LtTpLuZwknd7rd6x1ZTQzz7OTM9ScOul8iaFYF1sSvSoZRUREREREZMU15Qwuz/P+HPjzM503xkSAa4EPn3JdDnj34uts97+Hc+yldb73kubR3j5INLqNQuEYoVCBTOaXdHZuoqNj0O9oa17RqvLk6BR5y2KuVKazNcyOoX7CoaDf0URERERERGQdaNYZXOdyPbDP87wHzzlS1pVY7ErC4W4sa456vcrk5P3U6zW/Y61pjUaDfeNJprIFLNvFdl0uH+ynu73N72giIiIiIiKyTqzKgsvzvEc8z7ve7xzSfAKBEP39L8GYAJaVwbbzTE//q9+x1rTx2RyHpjM4bp3ZYpmNvT0MxaJ+xxIREREREZF1ZFUWXCJnE4lE6e3dTb1eo1qdJ5c7TC53yO9Ya1K5WuOpsWnyFYtsuUJXa5htA30EA/rTIiIiIiIiIpeOPoXKmtTVtZW2tkFsO4frWiSTD2Pbeb9jrSme5/HMeIqJuRxV28WyHbYm+uhqi/gdTURERERERNYZFVyyJhljiMevJRhsxbIyOE6Fycmf4HkNv6OtGZNzeQ4lT16aGGVjX7ffsURERERERGQdUsEla1Yw2Ep//3V4Xh3LylAuJ5mbe9rvWGtCpWbz1Ng02VKZ+bJFe6RFSxNFRERERETEN/o0Kmtae/sA0ehWXLeC45RIp3+JbZf8jrWqeZ7Hs5MzjGWy1Jw65arN1kSvnpooIiIiIiIivlHBJWteT88VhEJtVKtzuG6FVOoRvyOtasn5Agcm09hunUyhxFCsi019PX7HEhERERERkXVMBZesecFgC729V+N5dWq1efL5oxSLY37HWpWqtsOTY9PMlUrkyhat4RDbB/sJBYN+RxMREREREZF1TAWXrAvt7UO0tQ1g2wXq9RrJ5MM0Gq7fsVadA1NpRtNZbLdB0aqxJd5LrENLE0VERERERMRfKrhkXTDG0Nt7DcYEqVZnqdXyZDK/9DvWqpLKFXh2MoXtumQKRQZjXVzWH/M7loiIiIiIiIgKLlk/wuEOenp2Uq/XsO08s7NPUa1m/Y61Ktiuy9Nj02QKZfLlKuFQiO0DfYRDWpooIiIiIiIi/lPBJetKd/d2Wlq6qFbncd2FpYqe5/kdq+kdmkpzbCaLU6+Tt2ps7o/R19XhdywRERERERERQAWXrDPGBOnruxrwqNXmKJUmyeeP+B2rqWUKJfZPzFB1HDL5MoloB5vjWpooIiIiIiIizUMFl6w7bW0JOjo24DglXNcilfoZrlvzO1ZTctw6T49Nk8oXKVg2oaBh+2AfkZaQ39FERERERERETrjogssY02OM+XVjzItPc27IGPNPxpi8MWbeGHOHMSaxtKgiy6e39yoCgRaq1Vkcp8TMzC/8jtSUjqRmOZKaw63XmS9V2NTfQ7+WJoqIiIiIiEiTWcoMrv8DeAC45eSDxpgQcB/wZqAL6AbeCfzYGBNewvuJLJtQqJVY7EoaDYdaLcf8/LNUKjN+x2oqc8UyT48nsWyb2WKZ/mg7W+K9GGP8jiYiIiIiIiLyPEspuF6z+PWbpxx/B3AVUAU+DXwCKAC7gVuX8H4iy6qrazORSIxaLUe9XmN6+mE8r+F3rKbguHWeHJ0iNV+gZNkAbB/opy3c4nMyERERERERkRdaSsF1+eLXfaccfzvgAf+P53mf9DzvL4H3AgZ42xLeT2RZGROgt/dFAFjWLJY1w9zcfp9TNYeDUzMcSc3h1OvMlSpc1h9joLvT71giIiIiIiIip7WUgqsfKHmeVzzl+K8vfr3rpGP3sFB6XbWE9xNZdq2tPXR1baVet3CcEun0ozhOxe9YvprJFXlmIoVl22TyZeLRDrYmtDRRREREREREmtdSCq7WU683xuxiYc+t5zzPSx4/7nmeDcwD0SW8n8iKiMV2EQy2Uq1mF5+q+IjfkXxTc1yeHJ1iJl+iYNUIBg2XD2ppooiIiIiIiDS3pRRcaaDdGDN40rGbFr/+7DTj24D8Et5PZEUEg2FisavwPJdaLUcu9xyl0qTfsXxxYHKGY+ksjlsnV66yJd5LPKqnJoqIiIiIiEhzW0rB9dji1z8FMMa0A+9jYSnij08eaIzZwELBlUSkCXV2bqC1NYFt52g0akxP/yuNRt3vWJfUdDbP/skUNcchXSiRiHayJRHT0kQRERERERFpekspuL7Kwsbx/6cx5gBwmIU9tjLAd04Z++rFr6duSC/SFIwx9PVdgzFBLGuWWm2eTOaXfse6ZCzb4cmxaTKFErmyRSQUZMdQH+FQyO9oIiIiIiIiIud00QWX53k/BG5jYcbWLmAYmAX+N8/zrFOGv3Px6wMX+34iKy0c7qS7+3Lq9Rq2XSCTeRzLmvE71orzPI9nxpOMzmSx3TqFSo0tiV76urQ0UURERERERFaHpczgwvO8/wBsA94B/Aaww/O8U5cnhoGfA58C/nkp7yey0np6dhAOR6lW56jXa0xOPkC97voda0VNzuU5MJWm5rqk8yWGervYHI/5HUtERERERETkvC15/ZHneePA+FnO28DtS30fkUvBmCD9/S8hmXwIy0oTCLSQTv+CoaGX+x1tRZSrNZ4cnSJbKjNftmiPtHD5YJyWYNDvaCIiIiIiIiLnbUkzuETWokikm56eXdTrNWq1HHNzT1MqTfsda9k1Gg32jacYm52n5tQp12y2JnqJdbT5HU1ERERERETkgqjgEjmN7u7LiURi1Grz1Os1pqZ+Qr3u+B1rWY3NznNgagbbqZPOlxiORdnU1+N3LBEREREREZELtqSCyyy42RjzQ2NM0hhTM8bUz/Ja25sZyZphTID+/hdjTADLymDbBZLJR/yOtWyKVpWnRqfJVyyy5QqdbWEuH+wnpKWJIiIiIiIisgpddMFljIkAPwL+Dvh3wADQAphzvERWhXC4i97eKxeXKmaZn3+WQmHU71hL1mg0eGosycRcHst2qTku2xJ9dLe3+h1NRERERERE5KIsZZP5PwP+zeK/vwP8D2Aa0CwtWTO6urZRLqeoVmcJhTqYnn6Q9vZBQqHVWwYdS2c5NJ3GdutkCiU298fY2NftdywRERERERGRi7aUgut3AA/4D57nfWqZ8og0FWMM/f0vZnr6p1hWmmAwzPT0g1x22W/4He2i5CsWT45MUbSqZItluttb2T7YRzCg7fhERERERERk9VrKp9qtLBRcn1+mLCJNqaWlnd7eq2k0HKrVLPn8UXK5I37HumCe5/Hs5AzJXJFKzcFp1Ll8sJ/O1ojf0URERERERESWZCkFVxHIe55XWq4wIs2qs3MT7e2D2HYe17VIJh/Ctst+x7ogyfkCzyVncdw6s8UKG2LdDMWifscSERERERERWbKlFFyPAd3GmN7lCiPSrIwx9PVdSzAYoVrN4DgVpqd/iud5fkc7L45bZ994kmypTK5i0dnawtaBXgJGz30QERERERGR1W8pBdf/x8JTET+0TFlEmloo1Epv74toNFyq1TmKxTHm55/1O9Z5OTYzx2hmHqfeoFStsTneS7Rt9W6ULyIiIiIiInKyiy64PM/7MQtPUvyoMeaTxpj25Ysl0pw6O4fp6NiI4xRxnAqp1M+x7YLfsc6qaFV5ZiKFZdvMFcv0d3WwSU9NFBERERERkTXkop+iaIz5yeI/i8BtwMeMMfsXvz8Tz/O8f3ux7ynSDPr6rqFanaNazRAKRZiaeoAtW34L04TL/TzP48Bkmun5Apbt0vA8tg30Eg4t5QGqIiIiIiIiIs1lKZ9yX3XK963AS89xzerYsEjkLILBMP391zIz8z+pVmcxJsjs7FPE49f5He0FZvJFDiczuPU6s4Uym/p7SHR3+R1LREREREREZFktpeD61LKlEFll2tsH6OraQrE4SihUIp1+lGh0M5FIzO9oJ7j1OvvGU8wWy+QrFu2RFrYmYtpYXkRERERERNaciy64PM9TwSXrWix2FZaVwbJmCQbbmJp6kK1b39g0SxVHM/OMprO49ToFy+bKDQm629v8jiUiIiIiIiKy7JbyFEWRdS0YDP3/7N15lKX5Xd/39/eudW/tW3dP79PTM2ppJCTwEHsMRJKNZUknQSZBkcHAwZiAOQ6KzXJyEhtsg51EIQaCARvEFtkswTYWjo1iWZY0YkYjjWZG0mzdPVuvtVfd/d5nf375o25LpaKX6q7qfm5VfV7n3HN7nuf3/J7P6en6o77n9/39mJl5K+Dw/RW63XnW1p7LOhYAHT/g+UsLdIOAtU6PqZEKx2a0sbyIiIiIiIjsTSpwiWxDpTLL6OhJ4rhHFHVYWnqKIGhkHYtzc8vM1Zt4YUycJJw6OM1QsZh1LBEREREREZG7YkcKXGb29Wb2s2b2KTN7sf/5lJn9H2b29TvxDpFBNTn5JgqFKp63SpL4zM8/hnPZnaew3Gxzfn6ZKE5YbXc5PDnGwfGRzPKIiIiIiIiI3G3bKnCZ2bCZ/S7wNPCjwNuBN/Y/bwd+DHjazH7HzIa3G1ZkEOXzBaan38Z6q+Iqnc4ctdoLmWRJ0pQXLi+y0urS6vlUigVOHpgmn9NiTREREREREdm77niTeTPLAX8EvBMwYAH4JHC1P+Ro/95h4K8CB8zsXS7LpS0id0m1Osvo6HHa7UsUCh0WFz/H6OgJSqWxe5rj0kqd15drJElKo+dz5sgsk8PaWF5ERERERET2tjsucAHfC/wFIGJ9pdavOOfSjQP6RbC/Cfx8f+z3AB/ZxjtFBta1UxV9f41CocLc3Kc4efLb7tmpir0g5PnLC3R8/ysbyx+fmbwn7xYRERERERHJ0nb6lr4bcMBPOOd+aXNxC8A5lzrnfgX4CdZXeX3vNt4nMtDy+SLT02/FuWRDq+JL9+z95+aXubrWIIgSwnh9Y/lKSRvLi4iIiIiIyN63nQLXW4EE+PAWxn4YiIG3beN9IgOvWj3A6OgJoqhLFHVZWnqSMGzd9feutrqcn1smShJWWl3umxzl0MToXX+viIiIiIiIyCDYToFrFGg757xbDeyPaQM6yk32vMnJh8nnK/j+KnHsMTd3d09VTNKUF68ustzs0PICysUc9x+Y0sbyIiIiIiIism9s5zfgVWDczA7camB/zASwto33iewK+XyRmZlrrYprdDpXqNfvXqvi5dU6ry6uEqcpja7H0ekJbSwvIiIiIiIi+8p2ClxPsr6v1j/Ywth/2B/7xDbeJ7JrVKsHGRk5RhR1iKIei4tPEobtHX9P1w/48sV52p5PrdNjvDrEiZnJe7axvYiIiIiIiMgg2E6B65dZL1r9kJn9CzM7vXmAmZ02s38J/BDrG9L/8jbeJ7KrTE1da1VcIY495ud3tlXROceLV5e4WmvihzFBlHD/gSmq5dKOvUNERERERERkN7jjApdz7tPAL7Be5Pou4LyZXTSzJ/qfS8B54Dv7j/y8c+6x7QYW2S3y+TLT01/Xb1Ws0W5fptE4t2Pzz9dbnJtbJooTVttdjkyNcmRqfMfmFxEREREREdkttrULtXPuR4EPAnXWC13HgUf7n2P9a/60TcwAACAASURBVDXgR5xzP34n7zCzI2bWMTNnZjfdpN7Mxs3st8ysbmZNM/sdM5u+zrj3mdnzZuab2Utm9oE7nUvkZoaHDzE8fJQoam9oVexse94givnypXlqnS71rke1XOTUwWltLC8iIiIiIiL7UmG7EzjnfsnMfh34S8AjwLVN55eBp4H/5Jzzt/GKnwU6wPAWxv4B8BDwA0AKfAj4KPAt1waY2TcD/wb4FdaLc+8Ffs/M6s65j9/OXCJbMT39Znx/Fd9fpVAoMz//GCdOvHdb+2Sdm1vi4nKNME7peAEPHz/EeFUby4uIiIiIiMj+tO0CF0C/gPX/9j87xsz+S+DdwP/KeqHrZmMfBd4FvN0595n+tTng82b2rc65T/SH/iTwGefcB/v//Skzexj4KeDjtzmXyC2ttyq+heXlL+D7Nczy1OsvMTX18B3Nt9xs89LVJcI4ZqXV4dDkKMemJ3Y4tYiIiIiIiMjuMbD9TGaWB/4p8NPA6hYeeQ+wdK0gBeCcewq40L+HmZWBd7K+Omuj3wceNbPxrc4lcjuGhw8zMnKtVbHLwsJn8f3abc8TxQnPXV5gqdmh5QWUCjlOHZymVMjfhdQiIiIiIiIiu8NdKXCZWd7M/gcz+yMz+7dm9jfuYJq/CZTZ+smLZ4Dr7eB9tn8P4AGgeJ1xZ1n/u3joNuYSuS1TU2+hUBjG89ZPVbxy5RMkSXxbc7y2tMrri2vESUKj63NsepLpkepdSiwiIiIiIiKyO9xxi6KZfT/wYeBfO+c2b9L+e8B/e20o8G1m9pecc391i3NPAz8DfLdzLtriXkWTQOM61+vAqQ1juM64+qb7W5nrhpxzBEGM74fkcumthss+Mjb2ZhYXP0ezuUQUweXLn+HQoUe39Gyz6/HsqxdpdzssNzpMVEocGa8SheFdTi0iIiIiIiKSrTi6+e++21nB9a7+9+9uvGhm7wC+g/XC1meBa/tVvd/M3rfFuf8x8Dnn3B9vI989ZWY/aGZPm9nT9Xo76zgyoMrlKcbHT5MkHmHQZG3tBTrtK7d8Lk1TXriyyFKjQzeIcA7uPzBFuVi8B6lFREREREREBtt2Clxv638/sen69/a/P+yc+xbn3LuAv896wev7bjVpf8P37wd+2swmzGwCuNaDNW5mNzoqrg6MX+f6JF9doXXte/O4yU33tzLX13DO/Zpz7hHn3COTk6M3iCgC4+OnKZcmCcI6SRIyN/8nRFHvps9cXm3w+lKNKEmptXscmR5ndkz/zkRERERERERge6cozgCBc27zBvDfCjjgFzdc+2XWN4t/ZAvzPsj6PllPXufeVeA3gB+4zr1zwLdc5/oZ4KP9P78GRP1rj20akwIv38ZcN2RmlMsFhoZK5HI7clCl7DFHjn4j8/OPkaZr5HJD1Gqf48SJ93K9dtyOH3B+qUYvSWgGEZPjo5w+cpChoXIGyUVERERERETuvUKxdNP721nBNQb4Gy+Y2X3AUWDZOffitevOuTrQAma3MO/jrJ90uPHzof699wI/e4PnPgYcMrNv3pDnEdb3zPpYP0cAfAp4/6ZnPwA86ZxrbnUuke0oFoeZnv460jTC99doty9Rq73wp8Y553jx8iJXa038MCaIEk4dmGJExS0RERERERGRr9jO8qImMGVmVefctf6qt/e/P3uDZ/wbXP+K/oqwT2+8ZmYn+3/8E+dcp3/t0/3x7+h/P2lmHwc+YmY/zvqKrA8BjzvnPrFhup8BPm1mv8D6aqz39j/v3pBhq3OJ3LGRkaN43hKdzlUKhQqLi09Srd5HpTLzlTFztSbnF1aI4oTVdpcjU2Mcnrpe96yIiIiIiIjI/rWdFVzXlpv8dxuufS/r7Ykb2/8ws3HWV3wtbuN9m1WB5U3XPtB/928CHwGeAb594wDn3OOsb4L/rcB/BL4N+C7n3Mdvdy6R7ZqaeiuFwjCet0oc+1y9+kmSJAbADyOeu7xArdOl3vWoloucOjhNPredH1sRERERERGRvWc7vyn/Husbx/+ymf0zM/u3rK+CCoE/2DT20f73K3fyIufcbzvnbMPqrTLwVtb39to4ruGc++vOuQnn3Jhz7ruus0cYzrmPOufe7JwrO+fOOOd+/zpjtjSXyHbk8wVmZ78BM/C8ZXx/laWl9e3nzs8vc3G5RhindP2AE7NTjFdvdMaCiIiIiIiIyP61nRbF3+CrK6F+kPVilwP+nnNu80qt93OdlV3b8AjwvHNup+YTyczQ0BQTE2+gXj9LEDRYW3sez03z4lWfMI5ZabU5ODHK8ZmJrKOKiIiIiIiIDKQ7LnA55xIzezfwncCfBxrAHzvnntg4zsxKwH3AZ9ihDdr779jKiYwiu8L4+IP9FVxrOCvz/PN/zFL0Vlq+o1TI88DBaYr5fNYxRURERERERAbSdlZw4ZxLgd/pf240JmR9E3cRuQEzY2bmG5ib+zSvzc+x3C0TuS/TDB7kDUdmmRqpZh1RREREREREZGDd8R5cZvZJM/vPZvbATgYS2a+KxSpx8QyLrQ5h0KDTvcKh6gonZ6cws6zjiYiIiIiIiAys7azg+mYgcs69tlNhRPazjh9xsV7GTycIgkUqhZQjw1co0AG0/5aIiIiIiIjIjWznFMUl1k9MFJFtSlLHS/NNFptdAo6TujyzIx7VoqPXfArnXNYRRURERERERAbWdgpcnwHGzOzBnQojsl9dWOlwaaVJkia0/JDpqTcwWikTR3XicIWg93LWEUVEREREREQG1nYKXP8nEAP/xLRBkMgdW20HnF+o44UhjY7H1HCBI7NHKA0dwaUeaeLht58jibtZRxUREREREREZSHdc4HLOfRH4TuAdwBNm9u1mdlDFLpGt86OEl+bq1Do9emFMIZdwYmaESqlIsXIay1VIojou8fFaT6tVUUREREREROQ67niTeTNLNvznnwX+9YZ7N3rMOee2s7G9yJ7hnOP8Qou5Wos4TvECnwdmq0wNVwHI5QqUhh8iaD9HEjfAzxH5lylVTmScXERERERERGSwbKdF0e7wIyLA1ZrHheUGUZJQ7/U4OF7i8NTo1/yUFEuzFEoHSJMuaRritZ4lTYLsQouIiIiIiIgMoO2spnrnjqUQ2WdaXsTZ+Totz6ftBYyWjePTYxTy+T81tlR9iCSqk4Q1clbCa3+R4Yk/l0FqERERERERkcF0xwUu59xjOxlEZL+Ik5Sz802WWx2COCFOIk4fGGVkqHTd8bl8mVL1AYLuWdK4Sdi7QGnoJMWhQ/c4uYiIiIiIiMhg2k6LoojcgddXOlxabZCkKc2ux5HJIWbHR276TKF8mFxxiiRp49KQXutp0jS6R4lFREREREREBtuOFbhs3YyZHd+pOUX2muWWz8sLdfwwot7xmBkpcGx6jNwtDh81M8rDbwDLEUc10qhJ0HnxHqUWERERERERGWzbLnCZ2TeY2R8CTWAJeH3T/Ukz+1Uz++dmVtnu+0R2Ky+MeWmuQa3ToxdElPMpJ2dHKRe31imczw9THDoJLiBNOvjdcyRh/e6GFhEREREREdkFtlXgMrPvAZ4E/gowwnVOSnTO1YEHgP8eeN923ieyWznnODffYqHeIk5SemHAsakKE9Xbq/mWKifI5UdJ4ma/VfEpnEvvUmoRERERERGR3eGOC1xm9ibgw0AR+EXgEWD1BsP/b9YLX++50/eJ7GZzdY+Lqw3CJKHR8zk8XuLQ5NimcvCtmeUoD58BIInqxOEqQe/lu5BYREREREREZPfYzgquHwVKwC875/62c+5ZILnB2P/c//4z23ifyK7UC2LOzTdoewEdL2CsDMdmxijk7+zHL18cpzh0BJd6pImH336eJO7scGoRERERERGR3WM7Ba53Ag740K0GOufmAQ84to33iew6zjnOL7RYbnWIkoQojjg2PcxwubSteYuVB7BchSSq4xIfr/UMzrkdSi0iIiIiIiKyu2ynwHUY6Drnrm5xfA/QJvOyr8w3PC6tNomThGYv4PBEidnxkW3Pm8sVKA0/BKQkcYPIv0rkX95+YBEREREREZFdaDsFrgAomdktdxEyszIwATS28T6RXeVaa2LL82l7IaNlODI9Ru7WPzJbUizNUigdIE26pGmI13qWNAl2ZG4RERERERGR3WQ7Ba7XWd9g/qEtjP3LQB54cRvvE9k1nHO8vNRiqdkhTlLCOOTY1PZbEzcrVR/CrEQS1kjjHl77Szs6v4iIiIiIiMhusJ0C1x+zfgbc377ZIDMbBf531vfr+nfbeJ/IrjHf8Lm43CK+dmriRInZ8eEdf08uX6ZUfQCISOMmYe914vBGh5mKiIiIiIiI7E3bKXD9AtAEftDMfsbMJjbeNLOKmf03wFPAGWAR+LVtvE9kV/DCmHMLdVqe95XWxKPTY+Rz2/lxu7FC+TC5wgRJ0sGlIV5TG86LiIiIiIjI/nLHv3E751aB9wM+8L8AS8AMgJnNs178+lfAG4AO8B3Oue52A4sMMucc5xdbLDe+2pp4dKq6462JG5kZ5eH1TuEkbhBHq4S91+7a+0REREREREQGzbaWlDjnPgH8OeDTrO/HlWe9bfEQUOj/+dPAo865J7fzLpHdYL7hc3GlRZQk1Hse942XOLADpybeSr4wRrF8Hy71SBMPv/McaRLe9feKiIiIiIiIDILCdidwzj0P/EUzOwF8E3CY9ULXIvCEc+7V7b5DZDfwwoTzCw1avX5rYunutiZuVqycIo5WSKImuVwFv/M81fE/c0/eLSIiIiIiIpKlOypwmVmO9X21xoCac+5l59wl4NJOhhPZLZxzvLzYYqnR/kpr4qn7RhgZunutiZvl8mVKlfsJuudJkzZB7xVKlQcolCZu/bCIiIiIiIjILnZbS0vMrGhmHwJqwPPAE8BZM1sxs79rZnY3QooMuoWmz4WVJlGS0LiHrYmbFcpHyOXHSOIWpCFeWxvOi4iIiIiIyN53u71THwV+nPWVW7bhMw38NPBbO5pOZBfwwoTz8/3WRD9k5B63Jm5kltuw4XyTOFgk8i/f8xwiIiIiIiIi99KWfwM3s/cD72G9oPUq8L8Bfwv4WWC+f/17zOztdyGnyEByzvHqcpvFfmtiEIYcnR6+p62Jm+WLExRKB0iTLmka4rW+RJpEmeURERERERERudtuZw+u7+5/fxx4n3MuuHbDzP4x8Eng64G/Bjy2YwlFBthi0+f1pcZXWxMnShzMoDVxs1L1NEm0RhLVyFmJoPsilbG3ZR1LRERERERE5K64nR6qbwAc8Hc2FrcAnHMt4H9ifRXX1+9cPJHB5UfrrYnNnkfnWmvi1GgmrYmb5fJDFCsnwUWkSQe/e259Xy4RERERERGRPeh2fhOfAXzn3Nkb3H96wziRPc05xytLbRYabeLE4fdbE0cr5ayjfUVx6Bi5/AhJ3IQ0wms9m3UkERERERERkbvidgpcZaB5o5vOueaGcSJ72nzD57WvtCb2BqY1cSOzHKXqg4AjiRtE/jyhN5d1LBEREREREZEdl30vlcgu0wtizi3Uv/bUxAFpTdysUJomX5olTbq4NMBrP4tzcdaxRERERERERHbU4P1GLjLAnHOcX2ix1OgQJylhNHitiZuVqg9iViCOGqRxi6BzLutIIiIiIiIiIjvqdgtcB80sudGH9U3obzZGS0dkV7ta87i4eq010efwALYmbpbPVygMHQcXkCZd/M5LJHE361giIiIiIiIiO+Z2C1y2Ax+RXanjR5xbqNP2AjpewFgZjk6PDWRr4malyglyuSpJ1MClAb42nBcREREREZE9pHAbY//hXUshMuDS1HFuoclys0sYJ0RJxOkDowyXS1lH2xKzPMXh0wTt50niFqF/hVKwSLF8KOtoIiIiIiIiItu25QKXc04FLtm3Ltd6XFptEacJTc/n+GSZ2QFvTdysUJwlLk6RRDVy+WG85jPkZ/4yudzt1LlFREREREREBs/g91aJZKzZizg/X6frBzR7PpMV4+j0GDnbXR23Zkap+hBYjiSuk0QN/PZzWccSERERERER2TYVuERuIum3Jq60uwRRAi7m+MwolVIx62h3JF8YplS5H5cGpEmboHueyF/KOpaIiIiIiIjItqjAJXITF1Y6XF5tkqQpzZ7HkckhpkeGs461LcWh4+QK4yRxC5eG9FpPkaZR1rFERERERERE7pgKXCI3UOuGvLzQwAtDml2P6ZECR6bG2GWdiX+KWY7yyJvAjDiqkUYt/NYXs44lIiIiIiIicsdU4BK5jihJOTvXoNbp4ocxOUs4MT3CUHFvbMiezw9TqjwALiCNWwS9V4n8haxjiYiIiIiIiNwRFbhEruPCSoe5eos4dXR8n6NTFSZHqlnH2lHFoWPkilMkSQuXBvSanydNgqxjiYiIiIiIiNw2FbhENlltB7y80MAPIxpdj5nRAocnd39r4mZmxtDwGzErrLcqxl281rNZxxIRERERERG5bSpwiWwQxinnFhrUuz16YUwpn3BsepRSIZ91tLsil69Qqp4GF5HGTULvAqF3OetYIiIiIiIiIrdFBS6RDV5bbjO31iJOUnqBz9HJKpPVStax7qpC+TD54gxJ0iZNA7zm06SJl3UsERERERERkS1TgUukr9YNeX25SRDHNHoeB0aL3Dc5CnusNXEzM6Pcb1VMwhpp0qPXfDrrWCIiIiIiIiJbpgKXCJCkjlcWW9Q7PbwwppxPOTY9QnGPtiZulsuXKQ2/AYhI4iaRf5mgdyHrWCIiIiIiIiJbogKXCHC11uPqWpPErZ+aeHiyynhlb7cmblYsH6JQOkjab1X0W8+QxN2sY4mIiIiIiIjc0sAVuMzsO8zss2a2Zma+mZ03s79nZqVbPDduZr9lZnUza5rZ75jZ9HXGvc/Mnu/P/ZKZfeBO55K9wQtjXlls0A1CWp7PZDXHfRMje7418XpK1YewXLnfqujhNT+Pcy7rWCIiIiIiIiI3NXAFLmAa+CTwA8B7gN8E/i7wc7d47g+Ad/Sf+z7gG4GPbhxgZt8M/BvgU/25/wPwe2b2rtudS/aOV5c7rLS6xElKEsccnRqmXCxkHSsTuXyZUvUMkJDEDaJggaD3StaxRERERERERG5q4H6Ld8796qZLnzKzMeBvmdmPuOssJzGzR4F3AW93zn2mf20O+LyZfatz7hP9oT8JfMY598ENcz8M/BTw8ducS/aAlbbPheUGUZLQ6HkcHi8xMzaSdaxMFcuzJOEh4nABy1Xw21+mWDpMvri//15ERERERERkcA3iCq7rWQNu1qL4HmDpWkEKwDn3FHChfw8zKwPvZH111ka/DzxqZuNbnUv2hjhJOb/QpNnz6QYh1SIcmRolZ/uwN3GT0vBDWK5CEtVxiU+v+Tm1KoqIiIiIiMjAGtgCl5nlzazabyv8IPDPrrd6q+8McO4618/27wE8ABSvM+4s638PD93GXLIHXFrrMV9vk6QpvSDk6GSF0Uo561gDIZcrUh4+AzjiuE4cLhH0Xs46loiIiIiIiMh1DVyL4gZd4Fq14SPAT9xk7CTQuM71OnBqwxiuM66+6f5W5rop5xxBEOP7IblcupVH5B7rBBHnLq/Q7Xo0uj4TQ8ZktUIURllHGyBjuNxBIn+eJB4ijr+IY4Z8Qa2KIiIiIiIicm/FUXjT+wO7ggv488C3AD8GvA/4pWzj3JyZ/aCZPW1mT9fr7azjyE0453htqcNqxyOIE8wSjk0NUyoM8o9DNkqVB7DcEEncwCUBfvtZtSqKiIiIiIjIwBnY3+idc8865x53zv0c6y2KP2xmD9xgeB0Yv871Sb66Quva9+Zxk5vub2Wu6+X9NefcI865RyYnR280TAbAUivgylqbNE1oewGHxkpMjFSyjjWQcrk85eqDQEqSNIj8BSLvUtaxRERERERERL7GILcobvRs//t+4LXr3D/H+mqvzc4AH+3/+TUg6l97bNOYFLi2wdBW5ropM6NcLjA0VCKX2y1/xftDECdcrPXoxRG9JGVipMCxg5OUysWsow2sYukQ5taIwwXy+RGS4AXyY8fI56tZRxMREREREZF9olC82dmDA7yCa5Nv6n9fuMH9jwGH+hvSA2Bmj7C+Z9bHAJxzAfAp4P2bnv0A8KRzrrnVuWT3urjSZanRJkkcQRhyZKrKcPnmPyQCpeEHsVyZJGqQJh5+89lbPyQiIiIiIiJyjwzc8iIz+/+ATwAvAgnrxa0fA/4f59xr/TGfBnDOvaP//aSZfRz4iJn9OOsrsj4EPO6c+8SG6X8G+LSZ/QLrq7He2/+8+9qA25hLdplGL+S1pSZBHNPwfA6MFTkwpg3TtyKXK1GqPkjQeYEkbhL6lyl6lylVjmcdTURERERERGTwClzAF4DvA04CMfA68D8D/3zDmCpwcdNzHwB+HvhN1lem/XvW9+76Cufc42b2HcA/An6Y9RVh3+Wc+/jtziW7S5o6zi+0qHV7+GFMKZdwdGqMQn63LGLMXrF8iDhcJgmXsXwVr/UMhdJBcvnyrR8WERERERERuYsGrsDlnPtJ4CdvdN/MysBbgZ/Y9FwD+Ov9z83m/yi32Etrq3PJ7jFX97haa5GkKS3P54HZChNVbSx/u8rVN+BFdZKwRs5KeO1nGZ54NOtYIiIiIiIiss/txuUrjwDPO+ceu+VIEcALE15ebND1A1qez2Q1x6HJEbCsk+0+uXyZUvU0EJHGTcLeBSJ/PutYIiIiIiIiss/tugKXc+4J59wjWeeQ3cE5x2vLbZabHeIkJY5jjk4NUynp1MQ7VSgfJl+cIknauDSk13qaNI2yjiUiIiIiIiL72K4rcIncjoWmz+vLDaIkodHzODReYmZsOOtYu5qZURo+g1meOKqRRm389nNZxxIREREREZF9TAUu2bO6QczZ+TqNrkfHD6kW4ejUKPmc/tlvVz5fpVg5BS4kTdoE3ZeJwpWsY4mIiIiIiMg+pd/0ZU9KUsfZ+QaL9fXWxCAKOT4zzGhFJ/7tlOLQUXL5cZK4hUtDvMZTOJdkHUtERERERET2IRW4ZE+6uNrl4nKTOE2o9zyOTJQ4OD6Sdaw9xSxHeeSNYEYS10jiBn77haxjiYiIiIiIyD6kApfsObVOwPn5Or0wpNn1mawYx6bH1Zp4F+QLIxSHTuLSgDTu4HfPkoS1rGOJiIiIiIjIPqPf+GVPCeKEl+YbrHW6+GFMzmJOzIxRKevUxLulVDlBLj9KEjfXT1VsPoVzadaxREREREREZB9RgUv2DOccryy2ubrWIk5S2r7P0akqUyPVrKPtaWY5ysNnAEiiOnG0ht9Rq6KIiIiIiIjcOypwyZ4x3/B5balBGMc0uh4Hx4ocnhzFLOtke1++OE5x6Cgu9UiTLn77RaJApyqKiIiIiIjIvaECl+wJHT/i7FydZs+j7YdUS47j06OUCvmso+0bxcoD662KUaPfqvhZ0iTMOpaIiIiIiIjsAypwya6XpI6zC02Wmh2iJCGMQo5PDzNWHco62r6Sy+Upj74ZzIijNdKoQ6/5VNaxREREREREZB9QgUt2vQsrHS4tN4nThEbP58hEiYMTo1nH2pfy+WHKlYfAhSRxk8i/RNB9NetYIiIiIiIissepwCW72lon4OWFBr0wpNn1mKoYx2bGyWnjrcwUK0colA6SJi3SxMNrP0sSNbOOJSIiIiIiInuYClyyawVxwktzddY6XbwwJmcJJ2bGqJSKWUfb90rDZ7BchSSq4ZKAbv0J0jTOOpaIiIiIiIjsUSpwya7knOPlxTZXay3iJKUb+BybqjI1Us06mgC5XJHyyMMAxNEaSVTHb38p41QiIiIiIiKyV6nAJbvSfMPjtaUGUZzQ6PY4OFri8OQoqDNxYBSKExQrJ3GpT5q0CbovE/lzWccSERERERGRPUgFLtl1Wl7E2bk6rZ5H2wsZLsHxmVGKhXzW0WSTUuV+csVJkriJSwN6jc+TJN2sY4mIiIiIiMgeowKX7CpBnPDC1TqLzQ5hnBDFIcemhxmtlLOOJtdhZgwNP4xZkTiskSZdvMbncM5lHU1ERERERET2EBW4ZNdIU8fZ+SaXV5vESUKz53F0qszBidGso8lN5PJDlIbPADFJ3CAKFgk6L2UdS0RERERERPYQFbhk17iw2uW1pQZhHFPr9DgwVuD4zAQ508Zbg65YPkChfIQ06ZImXfz280ThWtaxREREREREZI9QgUt2haWmz7n5Gl0/oNHzGSsb989OUNK+W7tGqfogufwISdQgTQN6jSdIkzDrWCIiIiIiIrIHqMAlA6/tR7wwV2Ot3aUXRuSIOXlglJGhUtbR5DbkcnnKww+DGXFUI43aeK0vZB1LRERERERE9gAVuGSghXHKi1ebLNQ7REmCFwScnK4yMzKcdTS5A/niKKXKg+AC0rhJ6F0k6L2WdSwRERERERHZ5VTgkoHlnOP8YotLK3XiJKHR8TgyUeK+qTHQtlu7VnHoCIXiLEnSIk18vObTRMFS1rFERERERERkF1OBSwbWxdUuryzWCOKYeqfH7FiBE7MT5HP6Z7ubmRmlkTdiuQpJtEaa+HTrf0IStbKOJiIiIiIiIruUKgUykFbaPmfn6nS8gKbnM1KG+2fHKRcLWUeTHZDLlaiMvg2zPHG4iks8uvXHSJMg62giIiIiIiKyC6nAJQOn40c8f6XOWqeLF8aYizk5O8JopZx1NNlBucIw5ZG3AAlRuEoStdaLXGmSdTQRERERERHZZVTgkoESJSkvzjWZr7eJ4oRu4HNiqsrM6EjW0eQuKJSmKA2fARcQx2vE4Qpe80mcc1lHExERERERkV1E/V4yMJxznF9ocXGlQZIm1Ls9jk2WODw9hmlT+T2rNHQY0h6hd5GUAiGXyOVHqIy9LetoIiIiIiIisktoBZcMjEtrPV5drBNEEbVOj5mRAse1qfy+UKqeplA62D9ZsYvfeZGg91rWsURERERERGSX0AouGQhrnYCXeVRWtwAAIABJREFU5mq0PJ+2FzBcdJycHWNIm8rvG6XhN5GmAUlUB/J4jafI5asUy/dlHU1EREREREQGnJbGSOa8MOHFq3XW2l38MCZNI07MjDBeHco6mtxDuVyeodG3YrkKSbRGmoZ0608QR42so4mIiIiIiMiAU4FLMpWmjnMLTeZqLeI4pRP4HJuucmB8NOtokoFcrkhl9K2YFYjDFVzi0as9Rpp4WUcTERERERGRAaYCl2Tqcq3H68sNoiSh3utxaLzE0alRbSq/j+UKw5RH3wI4onCVJG7TqX2GNI2zjiYiIiIiIiIDSgUuyUytG3J2vkbXD2h6PmNl4/j0GIV8PutokrFCcZLy8BlwIXG8RhKu0ms8iXMu62giIiIiIiIygFTgkkwEccJLc3XWWl38KIY05vjMMCNDpayjyYAoDt1HqXI/LvFI4iaRfxm//aWsY4mIiIiIiMgAUoFL7jnnHOcX2lxZaxIlKW3P59h0hdkx7bslX6tUPUWhfB9p0iKNO/idlwh6r2UdS0RERERERAZMIesAsv9cqfV4balGFCfUuz0OjZU4PDmmfbfkukrVM7jEJ4kbYAW8xhfI5Ucplg9kHU1EREREREQGhFZwyT3V6IWcnavT9gLaXsBo2Tg+M0qpoH235PpyuTzl0a/DchWSaI00DejW/4QkamcdTURERERERAaEClxyz4RxyotXG6y0OgRRQpJEHJ8eZrRSzjqaDLhcrsjQ6NdhlicOV3FJj27jM6RpmHU0ERERERERGQAqcMk94Zzj5cUWV9eaxGlK2/M4NlVhdnwk62iyS+QLI5RHHgYS4miNJGzQq39WJyuKiIiIiIiIClxyb8zVPV5dahDEMfWOx+xYgSPTY+S08ZbchkJphlL1NC71SeI6UTCH1/pi1rFEREREREQkYypwyV3X8iJemqvT6nm0vZDhkuPE9Jj23ZI7Uqocp1A+Qpp0SOMOQfesTlYUERERERHZ51TgkrsqStb33VpudQjihCgJOT49wlh1KOtosouVqg+RL0ySxA3SxMdrfIEoWM46loiIiIiIiGREBS65a5xzvLLY5vJakzhJafU8jk4OcWBC+27J9uhkRREREREREdlIBS65a+YbHq8u1QmiiHrXY3a0wPGZce27JTsilytSGX3r156sWH9MJyuKiIiIiIjsQypwyV2x1gl44UqNRtej44dUCiknZka175bsqFxh+GtPVoyaOllRRERERERkH1KBS3Zc24947nJtfd+tKCGMQ47PDDNerWQdTfagrz1ZsdY/WfHZrGOJiIiIiIjIPaQCl+woL0z48uUac/UWUZzQ9jxOzlQ4NDGadTTZw9ZPVjxKmnT7JyueI+i+knUsERERERERuUdU4JIdEyUpz1+tc2W1SRQn1Ls9jk6WODqlfbfk7ls/WXGqf7Kih9d8mihYzDqWiIiIiIiI3AMqcMmOSFPH2fkWF5YbhElCvetxaLzEyQOTFPL6ZyZ3Xy6Xozz6lv7JijXSNKRbf5w4amQdTURERERERO4yVR5k25xzvLrc5pWFNYIootbpMVXNcWp2XJvKyz311ZMVC/2TFT16tcdIEy/raCIiIiIiInIXqcAl23Z5rcfZuRrdIKTR9RgtwakDY1TKxayjyT6UKwxTHn0LkBKFqyRxm07tMdI0yjqaiIiIiIiI3CUqcMm2LDY9Xrxao9nzaHshxXzKqQNjjFWHso4m+1ihOEl5+Ay4kDhaIwnX6DU+i3Mu62giIiIiIiJyFwxcgcvM3m9m/87M5sysY2bPmNl3buG5spn9EzNbNrOumf0HMzt5nXHfZGafNzPfzC6Y2QfvdK79rt4Nef5KjdV2h14Yk6Yh98+MMDVazTqaCMWh+yhV7selHkncIPKv4rWezTqWiIiIiIiI3AUDV+ACfhToAH8H+DbgU8DvmtmP3OK5XwS+D/hx4DuAGeA/mdlXlhKZ2WngPwIXgPcCvwr8nJn9wO3Otd91g5gvX6mx1GgTxAle4HP/TJWDE6NZRxP5ilL1FIXyYdKkTRp3CLrnCDrns44lIiIiIiIiO6yQdYDr+K+dc6sb/vuTZnaY9cLXP73eA2Z2FPgbwPc75z7Sv/Yc64Ws7wZ+vT/0J4B54Ludc3F/7uPA3zez33DOuduYa98K4oTnLteZW2sRxgltz+Pk9BCHp8cxyzqdyNcqVc/gEp8kroPl8VrPYvlhSpWjWUcTERERERGRHTJwK7g2Fbeu+SJw+CaPvav//Ycb5pkDHgfes2Hce4A/7Be3rvl94Cjw5tuca1+Kk5QXrzS5uFonSmLqnR5HJkocnxknp+qWDKBcLkd59C1YfpgkqpGmPr3GZ4nDtayjiYiIiIiIyA4ZuALXDTwKvHyT+2eAq865zqbrZ/v3MLNh4Bhw7jpjrs2xpbn2qzR1nF9o8epyjTBOqHV6HBgvcHJ2gkI+n3U8kRvK5YpURt+KWZE4XCVNfbr1x0jizT/mIiIiIiIishsNYovi1zCzvwj8FeD7bzJsEmhc53q9fw9gov+9eVx9wxxbneumnHMEQYzvh+Ry6VYeGXjOOV5d6vDS/Bo9P6De9RkrO45NjJNzjiiMso4ocgsFcuWH8TtfJoqXKRYdcfxJhqfeSS5XyjqciIiIiIiI3EQchTe9P9AruPonF/4u8EfOud/ONMwtmNkPmtnTZvZ0vd7OOs6Ou7DS5fxCjZ4f0OwFVEuOkwfGGC4Xs44msmWF4ihD1TPgYuJ4jSRs4DWeJE33RiFaRERERERkvxrYApeZTQEfAy4Bf+0Ww+vA+HWuT/LVFVrXVmVtHndtVVZ9w/et5vpTnHO/5px7xDn3yOTk3jpJ8Mpaj3MLNdqeT9sPKOUT7p8ZZbyqQyVl9ymUZyhVTuHSgCSpEwWL+O1nso4lIiIiIiIi2zCQLYpmVgX+PVAC/ivnXO8Wj5wDjpnZsHOuu+H6mf49nHNdM7vCn95H68yGObY01xbyUy4XGBoqkcsN5F/xls3VPc4vt+iEEV6SUig4Th8c58D43iriyf5SLJ0in4+Igyvkc2VcfIk0mmZo5I1ZRxMREREREZHrKBRvvrXMwK3gMrMC8K+AB4F3O+eWt/DYx/vf375hnsPAt7C+CuyajwHfbmYbd0T/AHAFeOE259rzlpo+z11Zpdbp0gsjkiTk/tkRDoypuCW7X3n4IfLFWZK4QZp4+K0vEQVLWccSERERERGROzCIy4t+BXgv8D8C02Y2veHeF51zgZn9NvAO59xJAOfcVTP7DeAXzMyAFeAfsN7e+C83PP+zrLc7/gsz+zDwjcAPAT/snHO3OdeettYJ+PLlNVaaHfwwJggDHjg4zKGJMbCs04lsn5lRHnkYv/U0SVTDrEiv/gSjs+8ml69mHU9ERERERERuwyAWuN7V//6/rnPvfuAiUAU2r+z6INAFfq5//zHgO51z/rUBzrlXzezd/TEfAxaBH3PO/frtzrWXNXohX7q8xlKzTRAldAOfU7NVDk+OYSpuyR6SyxUoj7wZv/UMcbiKWZ5u/bOMTP8FzAZugauIiIiIiIjcwMAVuK6tyrqFPwv81KbnAuBH+5+bzf848F/cYsyW5tqL2n7Ely7VWKi1COOYtu9xaqbC0ekxcqpuyR6UL4xQGj5D0HmBJK6DGV7ry1THvz7raCIiIiIiIrJFu26JgpkdAYrA72WdZa/pBTFfulTjaq1FGCc0uh7Hp8ocmxknn9t1/1REtqxYPkhh6Bhp0iWNOwTdswTe5axjiYiIiIiIyBbtuqqFc27OOXfYORdmnWUv8aOEL1+uc3m1SRTF1Ls9jk2WODEzoeKW7Avl6mlyhYn1TefTAK/5eZKonXUsERERERER2QJVLoQwTnnuSp2LK3WiJKbW7XJ4osTJA5MUC/lbTyCyB5jlGBp5M2YlknANl/h0658hTeOso4mIiIiIiMgtqMC1z0VJygtXG7y+VCdMEmodj4NjRU7OjlNScUv2mVx+iPLow0BKHK2RRA285lNZxxIREREREZFbUIFrH/OjhC9eqvHKwhpBHLPW7jI9nOPUgXEqpWLW8UQyUShOUaqewqU+adwk9C4QdF/JOpaIiIiIiIjchApc+1QviHn24hqvLdbw45hau8dkxXjg4ATVcinreCKZKg6doFA8QJK0SBMPr/UscbiWdSwRERERERG5ARW49qGWF/HMxVUuLDf6K7d6TFZznD40yciQilsiZkZp5I1YrkoS1UgTn279cdIkyDqaiIiIiIiIXIcKXPtMrRPwzIVVLq02CaP1tsQDo3keum+C0Uo563giAyOXKzI08hYwI47WSOMOvcZncc5lHU1EREREREQ2UYFrH1lu+TxzcZWrtfXiVr3b5chEidOHJtWWKHId+eIo5eEz4EKSuEYUzON3ns86loiIiIiIiGxSyDqA3Btz9R7PXVljpdkhiBM6nsfRyRInD0zqtESRmyiW7yOJGsTBHJYr47dfpFCcoTh0OOtoIiIiIiIi0qcVXHucc44LKx2+eHGFlWYHP4zpeB4npoc4dXBKxS2RLShVHyJXGCOJGrg0oNd4kiTpZh1LRERERERE+lTg2sOcc7y61OG5y6vUOj16QYQX+pyarXJidoJCXv/7RbYil8szNPIWzArE4Rpp0qNXf4I0TbKOJiIiIiIiIqjAtWclqeOl+SbPX12h2fNoeyFxEvDAwWGOzYyTz+l/vcjtyOUrlIffCMTEcY04XMFvfynrWCIiIiIiIoIKXHtSlKQ8f7XOS1fX6HgBTc8nR8TpA6McnRwnZ5Z1RJFdqVCepTh0Apd4pHGboHuewLucdSwREREREZF9T5vM7zFBnPDClQavLtUJoohax6NaTDl1cIyZkWFQbUtkW0rVB0jiJkncgFwZr/l5CoVJ8sXRrKOJiIiIiIjsW1rBtYd4YcyXLtV5eXENP4pY6/QYLTsevG+CmVEVt0R2gpkxNPIwZiWScA2X+HQbj5OmcdbRRERERERE9i0VuPaIjh/xzMU1Xl+qEUQJa+0uk5UcD903yeRwJet4IntKLj9EefRNQEocrZGENfzWM1nHEhERERER2bdU4NoDmr314tbFlSZ+FFPrdJkZyfPgfROMVspZxxPZkwrFaUqV+3GpTxq3CHqvEvQuZB1LRERERERkX1KBa5erdQKeubjKlbUmYRRTa3c5OFbkwUOTDJdLWccT2dOKlZPkizMkSYs0DfBaXyCJGlnHEhERERER2XdU4NrFlls+z1xcZa62XtxqdLscmSpx+uAElVIx63gie56ZUR55E5YbIglX1/fjqj9OmoZZRxMREREREdlXVODapebqHs9eXGGh3sKPYpq9Hseny5w6MEm5qMMxRe6VXK5EeeTNAOv7cUVNes0vZJxKRERERERkf1GBaxe6tNrlS5dWWG528KOYjudxYnqIk7OTlAr5rOOJ7DuF4jil6mlcGpDGTSLvIkHn5axjiYiIiIiI7Bta6rOLOOd4faXLi1dXaXQ9emGMH/qcmq1ydHqMfE71SpGslCrHSaMGcbQMuRJe+4vkStMUS9NZRxMREREREdnzVBHZJdLU8fJim+cvr9DoenSDkCjyOT1b5djMuIpbIgOgNPJGLFcliWqkiU+v8Thpov24RERERERE7jZVRXaBOEl5ab7JC1dXaXk+bS8gTUJOHxzhyPQEObOsI4oIkMsVGRp5C5gRR2ukUYde47OkaZp1NBERERERkT1NBa4BF8QJz11p8NLcKl0/oNH1yVvMg4dGuW9iDNW2RAZLvjhKufoQuJAkrhEFc3jNJ1XkEhERERERuYu0B9cA88KY5640uLBcJ4hj6h2P4ZLj1IFxpkerWccTkRsoDh0hidvEwVWMPCEXAaiMP0pO7cQiIiIiIiI7TgWuAdXyIp67UuPyapMoSVhrd5msGKcOjjNerWQdT0RuoVR9CFxMHC6C5Qi9i0CO4clHs44mIiIiIiKy56jANYBqnYAvX64xV28RRQm1Xo/ZkTynDkwwMlTKOp6IbEEul6M0/CYcjiRcAiD0XgfL8f+3d+fhleV3feff33POvdKVqqSq6qrudrfbvbnb7X1r2489YMABx+ZJ7EzGjAnMQ4ABP2aeCRlgEiAPDgYCiZNgT1gG4xDCQ4LxAzPExOA2jldsgycY7La73YuXbvda1bVXabvLOb/54xxJVyqpdulKqvfLj6x7z/q9V3WqdD/9/f3O5J5XjLg6SZIkSdpZDLi2mIMn5/niI8c4dPI0/UHJ8dk5rtvT5qYD03TarVGXJ+kCZFnG2ORz6ZIoe08B0Jv7KhBM7nn5aIuTJEmSpB3EgGsLeeToLPc8eowjp2foDkpm5ue5YW+bm67eS7vIR12epItQh1zPo8sXKXtHgKA39xUiMiam7xx1eZIkSZK0IxhwbQEpJb721AxffvwoJ2bnme8NmOsucNNVHW7YP02ROym1tJ3VIdcL6KYvUvaPANCdfQDImJh+yWiLkyRJkqQdwIBrxMoq8cCTp7j/yaPMzHeZ7fboD3o888AE1++fJosYdYmSLoMsyxjb9Xy6M3dT9o9BBN3Z+wiCzvSLR12eJEmSJG1rBlwj1C8r7nnsBF89eJz5Xo+T8wvkDLjtml1cu2cKsy1pZ8mynLFdL6A788U65AIWZr8MkdGZeuGIq5MkSZKk7cuAa0RmFvrc+/hJHn7qOAuDAcdn5ploVdx89RQHdu8Cwy1pR8qyog65Tt9N2T8OwMLMPXXItfv5I65OkiRJkrYnA64ROHhynnsfP87B4zMMqpJjp+eYGodbrtnD3snOqMuTtMGyrGBs9wuHQq5g4fQXAQy5JEmSJOkiGHBtorJKfP2pGe5/8hjHZ+YYlBXHZ+fYv6vglqun2d0ZG3WJkjbJcsj1+Wa4Yh1ypXKG8amXkWX+9SxJkiRJ58tPUJtkrjvgy0+c4KGnTjLf6zHX7TPf63LD3jY37J+m026NukRJm6wOuV7MwunPU/aPAnvpzn2dQf84k3u+mby1e9QlSpIkSdK2YMC1CQ6fXuDex07wxPFT9MuSk7PzFFnFbddO8rQ9u8mzbNQlShqRLCsY3/1iujP3UvYPk6oupMTpox9iYvoVtDvPGHWJkiRJkrTlGXBtoKpKPHRkhvufOMaxmTn6g5ITs/PsnQhuPDDNvskJJ5OX1IRcL6A3/zD9+a9TVT2K1n7mjn+aQe9ZdKZeTIRBuCRJkiStx4Brgyz0Kx5+5AQPHz3N7EKX+d6A2e4C1+1tc+NV03TGHJIoaVlEMDZxM3lrmoWZexn0DpG39tGdvZ+yf4yJva8izydHXaYkSZIkbUkGXBugrBJfeHSOk/0j9Es4ObtAFgNuOzDB0/ZNUeR2YkhaW9Hax8TUy1iYuZeyf4RUTUGCmcMfZmLvK2mNXTvqEiVJkiRpyzFp2QCz3QGHTs6w0Cs5cnqWyXbFs6/bww379xhuSTqnLB+nM/ViWp0bqcrT9HtPUZWnmT32ceZP30NKadQlSpIkSdKWYgfXBhhUFd3+gPnuLNftGecZ+6eYHGuPuixJ20hExtjEbWT5NN3Z++h3D5K3rmLh9N2U/SNMTL+SLB8bdZmSJEmStCUYcG2AlBJlucAtV3d4+lV7KPJ81CVJ2qZaY1eTFbvonv4SZf8IVFP0E5zuf4iJPa+kNXb1qEuUJEmSpJFzvNwGKLLguil4+lVThluSLlmeTzA+dSfF2HWU5UkG/SNUg1PMHvsocyc/R1X1R12iJEmSJI2UAdcGKHKIGHUVknaSLMsZ3/VsxiafS6r69LsHKQezdGcf4PThD9HvPjXqEiVJkiRpZByiKEnbSGv8aWStKboz9zd3WZyEVDF77KO0J57J+O4XkWWtUZcpSZIkSZvKDi5J2mbyfJLO1EtoT9xGVS4MdXM9WHdzLRwadYmSJEmStKkMuCRpG4oI2p0b6ex5OVkxRdk/Qtk/RjU4wezxjzF38q+cm0uSJEnSFcOAS5K2seVurtupyq7dXJIkSZKuSAZckrTN1d1cz6Cz52V2c0mSJEm6IhlwSdIOcc5uLu+0KEmSJGmHMuCSpB1kuZtrjbm5jn2M+VN3k1I16jIlSZIk6bLakgFXRDwzIn4zIr4YEWVEfOI895uOiP8YEccj4mRE/F5EXLXGdm+MiC9FxEJEfDki3nyxx5KkrSjPJ4a6uRbodw9RDmZZmLmH00f+G2X/5KhLlCRJkqTLZksGXMBzge8EHgAevID9/gD4VuCHgO8HXga8f3iDiPgm4P8FPg68HvhT4Pcj4rUXeixJ2spWzs01Qdk/TNk/Qdk7wukjH6I78wAppVGXKUmSJEmXrBh1Aev4QErpjwEi4v8B9p9rh4h4JfBa4FtSSn/eLHsc+P8i4ttTSh9pNn0b8OcppR9tnn88Ip4L/HPgwxd4LEna8vJ8F52pO+nNf53+/DeoygWK9j7mTn2OfvdxOnteTp7vGnWZkiRJknTRtmQHV7q4CWJeDxxaDKSa4/x34KFmHRExBnwbdXfWsPcBr4yI6fM9liRtJxEZYxPPpDP1UrKsxaD3FFX/FP2FJ5k5/Gd05x4edYmSJEmSdNG2ZMB1ke4A7l9j+X3NOoBbgdYa291H/V7cfgHHkqRtJ2/tYXz65RRj11GWp+j3nqIczDB34jPMHv8MVdkddYmSJEmSdMG26hDFi7EXOLHG8uPALUPbsMZ2x1etP59jrStVMOhX9HsDUn6urSVp8+XtZ1Kxh+7cV+j3DpIX0/R7X2N+5kk6U3fSGn/aqEuUJEmSpCWDfu+s63dSwDVSEfEW4C0AVx3Ye46tJWn0Wu395PkU3bmvUPYPU1XzFCkxd/xTtMafztjuF5AXzs0lSZIkaevbSUMUjwPTayzfy3KH1uL31dvtXbX+fI61QkrpPSmlO1NKd+6emjzvoiVplLK8zfiu5zA28SxSNaDfO0hZztJbeJSZox9m4fQ9pDQYdZmSJEmSdFY7qYPrfuCb11h+B/D+5vHXgH6z7JOrtqmABy/gWOuKDIpWRqtdUOSt86tekkaoPfYMxiYP0J99gEH/KKR58mwPZe9+uqceZ3z3i2iN30BEjLpUSZIkSVegotU+6/qd1MF1F3BtRHzT4oKIuJN6zqy7AFJKXeDjwHet2vfNwF+mlE6e77EkaafJ8w7jUy9ifPcLySJn0DtE2T9G2T/J7PFPMXvs45S9k+c+kCRJkiRtsi3ZwRURE8B3Nk+vB6Yi4k3N8w+mlOYi4hMAKaVvbb7/ZUR8GPjdiPg/qTuy3gF8OqX0kaHD/wLwiYj4v6i7sb6z+Xrd4gYXcCxJ2nGK9n7y1j76C4/Qm3+YqvskeTFFP8GgdxftzjMZ3/0Csvzs/wVFkiRJkjbLlgy4gKuBP1y1bPH5zcDDwETzfdibgXcBv03dnfYnwI8Ob5BS+nQTlv0L4EeAh4DvSSl9+EKPJUk7VURGu3MTefta+nNfrbu5BrPk7b105x6g332E8V0vpD1xMxE7qRlYkiRJ0na0JQOulNLDwLoTvUTEGPBC4J+s2u8E8APN19mO/37OMZfW+R5LknayPB8n3/08yt719d0We09R5R3ytJe5k5+lO/9VJqZeStHeP+pSJUmSJF3Btut/dr8T+FJK6ZPn3FKSdMny9l4603fSnnw2qSoZdA9S9U9Sdo8wc/QjzJ7471Rlb9RlSpIkSbpCbckOrnNJKX2GOuSSJG2SiIz2+PUUrQP0Fh5isPA4ZTlP3pomzX2FQbe+22K7c5N3W5QkSZK0qbZrB5ckaUSyvM345LPoTL+MrJik7B9h0D9COTjN3Im/YPbYx7zboiRJkqRNZcAlSbooebGbztRLGRsetjg4TX/hIKeP3sX8qS9QVf1RlylJkiTpCrAthyhKkraGiKA1fj15az+9ua8x6D1JWc6St/axMHMvvflH6Ey9mHbnhlGXKkmSJGkHs4NLknTJsnyM8d3PobP7JWTZOGXvEGX/GNXgJHPHP8XM0T+nHJwedZmSJEmSdig7uCRJl03e3kun9TL6C4/Sm3+IqvskeWsPaeFRBv2DjE3cRnvy2eT5+KhLlSRJkrSDGHBJki6riIx250by9jX05x5k0DtMGbMUrT0szHyZ3tzXaE/cxtjkHWT52KjLlSRJkrQDGHBJkjZEno+T734Bg94RenNfYdA7ROQd8nwPCzP30Jv/KmMTt9OeuN2gS5IkSdIlMeCSJG2oor2fvLWX/sIT9BceYdB7ksgnyKtp5k9/ke7cVxibeBZjk7cTWWvU5UqSJEnahgy4JEkbLiKn3bmB1vh1ddA1/w0G5UGyfIJUTTF/+gt05x4cCrr850mSJEnS+fMThCRp06wMuh6jP//oUNA1YP705+uga/JZtCduIcscuihJkiTp3Ay4JEmbrg66bqQ1fv2ZQVcqmT/1NyzM3Edr7FranZso2lfb1SVJkiRpXX5akCSNTERRB1hj1zPoPkZ//jEG3TroyvIevWqe/vzDRD5Ja/w6Wp0bKVpXEZGPunRJkiRJW4gBlyRp5LKsRbtzM0W7Cbq6Bxn0ngIK8mKSqPpU5Qy9ua+S5btpjd9Aq/MM8mIPETHq8iVJkiSNmAGXJGnLyPI27YlbaHVupOyfYNA7SNk7ShqcgBgjb+bqKgcn6c7eR17sodW5kdb4M8iLyVGXL0mSJGlEDLgkSVtORE7RvoqifRWp6lP2j9HvHqIcHKccnCCycbK8Q6oGDPpHWTj9JVrjT2ds4nby9lV2dUmSJElXGAMuSdKWFlmLYuwairFrqKoug94Ryu5BysFJynSCLO8Q+SRp/iH6C98gb+1nbPJ2WuPXE+E/c5IkSdKVwN/8JUnbRpaN0R6/HsavpxzMUfaeot87SNU7TBkFebGbVFUMek+RF1O0O7fSmriZPO+MunRJkiRJG8iAS5K0LeXFBHlxE63OMyj7x+kvPErZP0bJCfJ8F6SS+cHnWZi5l/bETbQnbqNo7Rl12ZIkSZI1Ub86AAAcQElEQVQ2gAGXJGlbi8iW5usqBzP0Fx5j0DtE2T1Nlk+Q5bvozj5Ib+5rFGPXMjZxG0X7GiLzn0BJkiRpp/C3e0nSjpEXu8h33UGqbqHffYL+whMMeoeIbIws302qHmew8ASRT9Iau5bW+A0U7QNE1hp16ZIkSZIugQGXJGnHiaxNu3MTrfEbKHtH6C88Rtk/SklBXkwSVZ+qnKE39zUin6AYu5b2+A0U7asNuyRJkqRtyIBLkrRjReQUY9eQt6+mHJxi0H2Msn+MNDgB0SLPF8OuWXpzXyPLJyjaTdg1djWRtUf9EiRJkiSdBwMuSdKOFxEUrWmK1jSp6lP2TzDoPUU5GAq7sglSNaAq5+jNf50s7yyFXfnY1WTZ2KhfhiRJkqR1GHBJkq4okbUoxg5QjB2ow65BE3b1j5F6p4CCPO+Qqj5VOU9v/iEi61CMXU1r7Om0xq4ly8dH/TIkSZIkDTHgkiRdsSJrUbQPULQPkNKg6ew63IRdh1gMuyLv0a/m6c9/g8jGKVr7aXVuaMKuiVG/DEmSJOmKZ8AlSRIQUVC091O095NSSdk/yaB3qAm7TgMFWRN2pXKBfvcxItoU7atojd9Aa+xpZMWuUb8MSZIk6YpkwCVJ0ioROUV7H0V7Xx12DU5Sdg8z6B+j6j1FSdaEXROkhR797pNLYVe7cyut8eu8G6MkSZK0iQy4JEk6i4icorWPorWPdqooB6coe4cZ9I5S9Q5TEnXYlXVIVR12ZfkErfEbaE/cQl7sJSJG/TIkSZKkHc2AS5Kk8xSRUbT2ULT20J64lXIwQ9k/TNk7Qtk/SklGnk82d2N8gN7cV8lb+2hP3EJr/AbvxChJkiRtEAMuSZIuQh12TVG0pkidm6kGMwy6TzLoHyb1ThHZGFk+SapKBr3DRHY37bHraU3eQtHaT0Q26pcgSZIk7RgGXJIkXaKIjLw1Rd6aop1uZdA7wmDhCcr+CUpOkOUTZPkk3WqB3sJD5MUeWp1nUIw9nbyYcgijJEmSdIkMuCRJuowiClpj19Iau5ZyMMOgd5BB9ykGvUMQ7aUhjIP+MSLuIS/2UIxfT2vsevLWtJ1dkiRJ0kUw4JIkaYPkxS7y4pm0OzdT9o7R7z5BOThOOThJ5ONk2QSp6jPoH6E7cw9ZMU1r7Dpa408nb+0hIh/1S5AkSZK2BQMuSZI2WEROMXaAYuwAZTlP2T1E2T9Sh10pNfN1dUhVn7J/jO7sfWT5borxp9Eav4GitZcI/8mWJEmS1uNvy5I0CikBaelppLT+tiNxZj2xuGzL1Tps6D1dqnft9Rci1tpvxfuQmu3WOVdatb7YR8r3UpULlOVRyu5Rqt4hoISow64sO0Gaf5x+/A2DrEPR2kfROkDe2kNW7CIb7u5aqmUr/2wkSZKkizfZO3LW9QZcGyBSolX1yAcL5KkcdTkXaPFD2Lk+zG3s+esa1li+pT9Yn9uFvKY1fwbn5cwP9Wsf68zzr6gvVSu3Y2UIE0vrh7fZ+J9PMPR6qmqNLaqhbZs/z+nMoAHSivclUgWpao5fNftUkBKREkEFpAt6icOBUP04NY/r8y/VsSX/WJ9foLMVLf85PktId6HO8XfPiuOuGaid+7ypSlTlPIPyMGU1T6IiKIisBVmbaF5ZkBFZizyfIM+nyPNJ8mxsaDjj1v3ZSJIkSRfrluMn2VVUY+utN+DaAK3BPLeefpB9WZcs317zp6z8kDaaD0lrf1DcHh+sL8g6LyMuY1i0dlB5ZgEXH6bpkqy+xrZ4gBs75jrcqC6uxe3WO+35nDeHbJoUk1TlHP1qjrI8SUolkNchVuREVgDHKXmckiCiRZaN08onyfIJ8miv7PCSJEmStrnxwQxFltb9JdeAawNkqaQzmKPdO7XtAq7aqLu4lq35QXGLhwAXZq0hVGusv0TnDrDW6uJap7NszcWb/DO5hE6is4W4ZwQ4aXj5JbzGoVBx+Ryx4tvi2q1tC9d3zvfxctfe9OGte9izne88a4k2Y3mblEqqqsug6jJIPaqqSzmo6rstRgGRERRUMcegfwwIIivIsw5F1qHIJigyAy9JkiRtb3nVo4i07i3HDbg2SGcwx1j/JFm5nW73fu4PZOt/mNsoW/gD9UVbI0KKjfnwPWzNgYhrnjaWvq8VFFQRa9a7KeFMLNe2vGz4/CsH/63cdihQitU/gxjaP0jZ8EDIjBTNurjwXrdENnT6xcdDx1/xXm6tP+9n/zOztWpdbc0/j5d4na3/Z/zs7896A68vrgYg9anKBQblDGU1y6DqUqVBHXRFux7SGK2mywuCILIgzycoimla+TRFPkmWtS65HkmSJGmzzM1//qzrDbg2QJUVzLR205++nSzfRh8gzju02Iwg48wna4cW29wZQcvSiks98BkPL+hnedkDN0mXT5soJmlxFS0gVf1m7q4ZynKWspqnYg7KDLIWWbQISso0oDc40QRebfJ8kqKYpsh3k+XjZNEii3bdGSZJkiRtMedqqjDg2kCDokNWrDv/mSRJlyyyFnnWIm9NAU3gVS0wGMxSlqcpqwXKcgbIICvqwCu1qcou/f6x+hiRE1EQUTRhV6eexD4br+/oGE1QZvglSZKkLcqAS5KkHWQp8Cp2A9eSqgFVtUA5mKEsZxhU85TlLEuBFy1SVs/jReTNuqHjrQi/JijyKYpidz3MMcYIOz4lSZK0BRhwSZK0g9UTzu8iL3YBrAy80hxV2aUqe1SpJFEBWX2nxsgJ8jPCrz6H69nqshYRYxTFFEUxTZ7tosg7zu0lSZKkkTDgkiTpCnJG4JUSpAGkAVUzvLFq7tZYVb0zw6/FYY5VC6JLWc7Q7T5BkNXdY3mHPJ+myKfI8zEiWmRNB5hDHCVJkrRRDLgkSbqCRQREC2jCKaaW1q0OvwblHFWaoyznqNI8KZUQRd3NlbWIVNRze8WJ+thkRJYBLSJysmys+Ronz8aJbJwsqwOweo6vfDRvgiRJkrY9Ay5JkrSmM8KvxYnsUwlVj7KcZ1DNUZVzlOUCZepTd3nlRBNqRZVBZEBOuaqDK4CIohkSWRDRqoOvvEORdYhsnDxrNV1gTnIvSZKk9RlwSZKkCxKRQ96hyDsU7AOW5/aqqrrDqyy7pNQjNcMbl+f3qr+CrD5OM9cXkUNkDIbPw6oALGuTRx2A5U0nWJa1myGQLTI7wCRJkq5YBlySJOmSLc3txS4Wp5mvO71KEgNS1adKfaqqS0p9qqpXL6NHlSoSJXWktdgBdoEBGDmRtZaGQGZZp3ncbibMz5o7Qi4+thtMkiRpJzHgkiRJG6Lu9MoJ2pDD6v6qlKpmjq+SqhqQUo+y6jWdX716knuGJ7k/WwCWQZnXmwzXsBhmRQ5kBFHvk+VLnV9EQZa1CFp1R9hSKFaQLQ2fNBCTJEnaygy4JEnSSNTBUxuAvEm/hn8xWRmADXeA9ZousD5puAMsUQddWdPRRUaKHCIIMogmICOaecHWqYtYCs9oArKIogm+2kTWJov2GWFYRN4EYg6VlCRJ2mwGXJIkaUtaGYB11ukAKyENSEshWI8q9UhV3QGWUg+oSClR/68C0nIYRkBWfw+yJhRrurwW5wyj+VrVHQbrhWH1HSMjWk0YNjYUhhVN59hiKLbGQSVJknTBDLgkSdK2FLEYQLUWBy+ukFICKkj1Vx1ulZAqqqokpQEVdYdYSoP6edUEZvSaUKzZbzEQG54kfykMy4bCsDroOlcYVs8Z1kyOn40NBWFjZFlrcevm2FE/j2xoedOVtrRckiTpymbAJUmSdqS6O2qxu2pl5nS2SCilsgnFmrm/luYIq4dJLodhTThGn9QEaPX2aWlS/DPDsMU5wwLKxVBsVd3DAVYsVrtYfba0nqHt6gn0W03YVTThWUGQNYFZQZYtB3FBvvT+RERdE2FHmSRJ2rYMuM4iIp4D/CrwSuAE8FvAz6WUypEWJkmSNszykMPWUKy0tuVhkovzgFX13GBLYVjTHVY1wRg9UqqoFjvLog6WlibOJyPF4nxhNF1a9aM60Fp8PFTReXZwrQzOFkOzxcCsPmc9hDKnDr6K5pw5WVZ3py2HafWwzXoC/qbDbLGuWHwcS+uGO88Wz2nnmSRJupwMuNYREXuBjwBfBt4I3Ar8MvVvlD8zwtIkSdIWsTxMkvMIwxY7wwYkquWusKrfTJy/2BU2IJGox0VSP05Dj5uvxSXL84mxHFytCp2CIMXy+uUwarHi4ecX+B4w3E0Wq465+M4MB1wsD71cHK65dDOAAiKrQ7ahdTF0N8vloZuLIdtwZ9rQ+exGkyTpimLAtb63Ah3g76eUTgH/LSKmgLdHxL9ulkmSJJ2X1Z1h2To3W1xqFE9DE+I3k+PXoVYzDLKZNj9VFTAYuptk1Ryj/p6oSNUAUiIxWNqPZuJ9qJZDtKXOrpXDIJtX0IRZUIdmQERT02I4NrzN6q6zoWUr9jnP929pn+X5yVZ2oZ0Z0i13qy0GcdmKrjKGhmcSOdlSYJkvdZnF8HlWzIO2XNVSyHfG6139EmPNpUvHOeO9Wj76ymMPLVvcxkBPknSFM+Ba3+uBP1sVZL0PeAfwLcAHRlKVJEna0aKZM2xx7rAV6y7ymKkJxJZDs4qlYKsJzKpqVSiWymbbcmi7ajFWg6qsh2iSgMVtzuw6W9FttqLzbFWgBs1QSVgOcZa/pxWB2+outNW3GRgO5i6v4S6x5QXDwR5DNa3c69w/wThjm5XHXXXMoedBtvTerHjvYviYMXScxRsVDC/PlvZZ3q/plFuqJruI9zaW87mhcy4PUx16/9Z471aHeSvDxVXnWfPx4vlWHeeMsHL1ubaSoZ+1YaYkrcmAa313AB8bXpBSeiQi5pp15wy4qu5pUn9hg8qTJEm6fOqP9s0k+OtvtCxfOWQSWOosWwqw1llX/68O0BZDskQaCtUWJ+yvls6RhsMzUnOXy7XWsXzOswZLKwOxpS2GO7wW9z0jUFgdGJ3rXGezVnfb2lusWLLqnGYe61gVCq4IDFf/nFcs32rWCzrXWH+Jx13xTmz7ufLO9726uPcv1hyUPhwkS+ey9t89sSX/Hhq9XvlE3Xy9DgOu9e2lnlh+tePNunVVCXqDgENf3pDCJEmSrjQXEx8tB17rLRl+ns76/2sfb+1jrl3L2StdIc6ybo26Vu67Xhi33vNzrYuhM12uD1znCpPO4zznDA8uZP1W/iB5OcMsSdr+8jytm2MZcF0mEfEW4C0AWUb5vW//jHN0SSM0t1CNTYxn3VHXIV2pvAal0fIa1CVZO83VeVp88+a71VhnzOtQF8VrcB0nZ8vJ9dYZcK3vODC9xvK9zboVUkrvAd4DEBGfO3i0f+fGlifpbCLic6dmS69DaUS8BqXR8hqURs/rUNpc231Q9Ua6n3qurSURcQMw0ayTJEmSJEnSFmDAtb67gL8dEbuHlr0ZmAc+OZqSJEmSJEmStJoB1/reDXSBP4qIb2/m2Ho78M6U0rnm13rPRhcn6Zy8DqXR8hqURstrUBo9r0NpE0VKzl22noh4DvBrwCup76j4W8DbU30Pa0mSJEmSJG0BBlySJEmSJEna1hyieJlExHMi4qMRMRcRT0TEz0dEPuq6pJ0oIr4rIv5rRDweETMR8dcR8Q/W2O6HI+IrEbHQbPO3RlGvtNNFxPXNtZgiYtfQ8oiIfxYRj0bEfET8eUS8aJS1SjtJRBQR8VPNv3XdiHgsIt61ahuvQ2mDRMR3R8TfNP8GPh4RvxsR163axmtQ2iQGXJdBROwFPgIk4I3AzwM/AfzcKOuSdrAfB2aAHwPeAHwceG9E/KPFDZrA693A7wKvB+4F/iQinrf55Uo73r+hviZX+yngbcA7gL/bbPORiLh2E2uTdrLfAX4U+LfAa6mvuflV23gdShsgIt4A/D7wF9SfAX8SeDXwpxEx/Dnba1DaJA5RvAwi4qeBfwrcuDgBfUT8U+pJ6a89j0npJV2AiNifUjqyatl7gVemlG5unj8AfCal9IPN8wy4G7g7pfS/bHbN0k4VEa8G3g/8EnXQtTulNBMR48Ah4JdTSj/fbDsJPAz8ZkrpZ0ZUsrQjRMTrgA8AL0wpfXmdbbwOpQ0SEe8DbkspvXRo2RuAPwaek1K6z2tQ2lx2cF0erwf+bFWQ9T6gA3zLaEqSdq7V4Vbj88B1ABFxC3A78AdD+1TAH1Jfr5Iug2Yo/q9Sdy6vvi5fBUyx8jqcpf5A7nUoXbofBD62XrjV8DqUNk4LOLlq2YnmezTfvQalTWTAdXncAdw/vCCl9Agw16yTtPFeCTzYPF687u5ftc19wL6IOLBpVUk721uBMeDX11h3B1ACX1m1/D78t1G6HF4BPBgRvxYRp5p5YP9o1fw/XofSxvlt4Jsj4vsiYioibgf+BSuDZ69BaRMZcF0ee1lO64cdb9ZJ2kDN5PF/D/jlZtHidbf6ujy+ar2kixQRVwG/APx4Sqm/xiZ7gZmUUrlq+XFgIiLaG12jtMNdC3w/8CLgu4EfAF4K/JeIWOwe8TqUNkhK6U+pr8H3UHdyPQDkwP80tJnXoLSJilEXIEmXIiJuAt4L/HFK6XdGWox0ZflF4LMppQ+OuhDpChXN1xtTSkcBIuJJ4JPAa4CPjrA2aceLiG+jvqHRvwPuAq6hnoP5v0TEt68RaknaYAZcl8dxYHqN5XtZ7hiRdJlFxD7qXyi+AXzv0KrF626alV1ce1etl3QRIuK51PP/vDoi9jSLJ5rv0xFRUl9nuyIiX/VL/l5gLqXU27yKpR3pOPD1xXCr8WmgBzyHOuDyOpQ2zi8D/zWl9JOLCyLiC9RTZLwR+CO8BqVN5RDFy+N+Vo2hjogbqH/ZXz0HkKTLICImgD8B2sDfSSnNDa1evO5Wz21wB3AspXR4E0qUdrLbqCfX/UvqX96PszwP12PUE8/fTz1U45mr9j1j3kpJF+U+lieyHhZA1Tz2OpQ2zh3AF4YXpJQeAOaBW5tFXoPSJjLgujzuAv52ROweWvZm6r/cPjmakqSdKyIK6jsi3ga8LqX01PD6lNLXqSec/66hfbLm+V2bWKq0U30a+LZVX+9o1n0n8G+AvwBOsfI6nAD+Ll6H0uXwJ8DzI2L/0LJXU4fPdzfPvQ6ljfMN4CXDCyLi2UAHeLhZ5DUobSKHKF4e7wZ+FPijiHgHcAv1+Ot3ppROjbIwaYf6v6k/RP9j4KpmsutFn08pdamvwf8cEQ8DnwH+IXUg9j2bW6q086SUjgCfGF7WzIcH8KmU0kyz7F8Bb4uI49T/pfrHqf/j2q9uVq3SDvYe6t8/PxARvwTspg6aP5JS+jRASmnB61DaMO8G3hURT7A8B9c/pw63Pgheg9JmM+C6DFJKx5u7uP0a8AHqOX/eRf0BW9Ll99rm+79bY93NwMMppd+PiF3ATwJvA+6lHsp4zybVKAn+FfUv8T8NXAV8DviOlNKhkVYl7QAppVMR8RrgV4D3Uc+99cfAj63a1OtQ2hi/Qn3d/QjwVurPgJ8GfjqlNDu0ndegtEkipTTqGiRJkiRJkqSL5hxckiRJkiRJ2tYMuCRJkiRJkrStGXBJkiRJkiRpWzPgkiRJkiRJ0rZmwCVJkiRJkqRtzYBLkiRJkiRJ25oBlyRJkiRJkrY1Ay5JkqQtIiLeHhFp1VcVEaci4rGI+IuI+PWIeFNEtEddryRJ0lZhwCVJkrQ1HWq+ngIScB3wSuB/A/4QeCIi3jq68iRJkrYOAy5JkqQtKKV07dDXNNACXgD8BPAQcBXwGxHxexERo6xVkiRp1Ay4JEmStoGUUplS+lJK6Z3A84D3Nau+B/ip0VUmSZI0egZckiRJ20xKaQ74h8Dnm0U/FRH7FtdHRBYRfysifiUiPtvM39WLiKMR8cmIeGtEtFYft1meIuJYRIyvd/7m+A8327591bo7IuI9EfFgRMxFxEJEPNrU8UsRccfleRckSZKWGXBJkiRtQymlHvBLzdMp4O8NrX4G8BHgHwGvAKaBOWAf8GrgN4CPRkRn1WF/D5gB9gJvOsvpXwvcCJTAf1hcGBHfAXwB+GHgNqAA5oGnN3X8NPDdF/ZKJUmSzs2AS5Ikafv6EHXIBPAtQ8sH1GHVG4CrUkq7U0p7gN3ADwBPAN8M/OLwwVJKp4H/3Dz94bOcd3HdXSmlR4eW/wYwBnwYeH5KqZ1S2gt0qIdV/izw8IW8QEmSpPMRKaVR1yBJkiSgGe73swAppfOaOD4iHqTulvpMSumbznOfO4G/AmaB/SmlhaF1L6TuwgK4I6X0wKp9rwEepZ70/g0ppQ80y6+mvusjwHUppSfPpxZJkqTLwQ4uSZKk7e1Y833fWbcaklL6HPAUMAm8aNW6u4G/bJ6+ZY3df4A63HoM+ODQ8tNA1Tx+2vnWIkmSdDkYcEmSJO1AEdFuJo3/cEQ8ERHdZlL4FBEJuLrZ9Olr7P7u5vv3RUR76JgB/FDz9D+klBaHR5JSmgc+2jz9UET8fES8Ynh/SZKkjWLAJUmStL0tdm4dXVzQDBf8HPWcWN9B3VFVAUeohxEeYrnbanKNY/4BdWfYfuDvDy1/DXAr9bxfv7XGfj8E3A0cAN4GfBY4HRGfjoh/MnynR0mSpMvJgEuSJGmbiohdwC3N068NrXoX8Hzq0OsHgaellDoppQMppWtTStdSTzQPcMZcX82cXL/TPB0epjg8ufxja+z3CPAS4HXArwB/Tf375v8A/GvgqxHxmgt9nZIkSediwCVJkrR9vQ7Im8efAIiIFstdV/97Suk/ppQODu8UETl1d9bZ/CaQgG+NiGdGxH7gfxxat6aUUpVS+rOU0j9OKd1J3WH2vcAjwF7gvQ5blCRJl5sBlyRJ0jbUhET/rHl6Enh/8/gAMN48/vw6u3/T0DZrSik9CHyMusPrh4HvA9rUd1C863zrTCmdTim9F/hfm0XXUHeXSZIkXTYGXJIkSdtMRHSohxC+uFn0L1NKJ5rHp6g7rwBeuMa+BfCL53mqxcnmv5/loYq/PTy5/NBxz9WVNT/0uFp3K0mSpItgwCVJkrQNREQWEc+LiB8H7gX+QbPqP1HPbwVASmkG+Ezz9J0R8ZqIyJpjPA/4IHAnMHsep30/cJD6jovPYv3J5QFeFRFfjIgfi4hnD50zIuJV1BPeAzwGfPG8XrQkSdJ5KkZdgCRJks4UEcPzZo0BU6z8j5NHgJ9JKa01H9b/AXwSuB74KNCNiB6wGxhQTzz/C6x9B8UlKaVBRPwW8DPNojUnlx/yfOCdzVc/Ik4B0yz/znkK+J61OsAkSZIuhR1ckiRJW9M1zdfV1AHRQeCz1J1QbwKuXyfcIqX018DLgT+gDsIy4HTz/FUppf90AXX84dDjdSeXB/4K+J+b+v66Oe8UsAB8gbrL7NkppU9dwLklSZLOS6SUzr2VJEmSrkgR8RPAv6WeXP5mu68kSdJWZAeXJEmS1hQROfAjzdN/b7glSZK2KgMuSZIknaGZJP7ngFupJ6R/99n3kCRJGh0nmZckSdKSiHgT9ZDEfdST0gP8bErp8OiqkiRJOjsDLkmSJA3bBdwI9IH7gV9LKf36aEuSJEk6OyeZlyRJkiRJ0rbmHFySJEmSJEna1gy4JEmSJEmStK0ZcEmSJEmSJGlbM+CSJEmSJEnStmbAJUmSJEmSpG3NgEuSJEmSJEnb2v8P0Vbie5cP7eIAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 1440x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "bptk.plot_scenarios(\n",
    "    scenario_managers=[\"Covid19\"],\n",
    "    kind=\"area\",\n",
    "    title=\"HEALTHY vs. INFECTED\",\n",
    "    x_label=\"Days\",\n",
    "    y_label=\"Persons\",\n",
    "    scenarios=[\"base\"],\n",
    "    agents=[\"person\"],\n",
    "    agent_states=[\"HEALTHY\",\"INFECTED_LIGHT\",\"INFECTED_HARD\"],\n",
    "    series_names={\n",
    "        \"person_HEALTHY\":\"Healthy\",\n",
    "        \"person_INFECTED_LIGHT\":\"Infected with light symptoms\",\n",
    "        \"person_INFECTED_HARD\":\"Infected with strong symptoms\",\n",
    "    },\n",
    "    visualize_to_period = 100,\n",
    "    progress_bar=True\n",
    "    \n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>person_INFECTED_LIGHT</th>\n",
       "      <th>person_HEALTHY</th>\n",
       "      <th>person_INFECTED_HARD</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>t</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>1242</td>\n",
       "      <td>6440.0</td>\n",
       "      <td>318</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>1369</td>\n",
       "      <td>6313.0</td>\n",
       "      <td>318</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>1518</td>\n",
       "      <td>6164.0</td>\n",
       "      <td>318</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>1672</td>\n",
       "      <td>6010.0</td>\n",
       "      <td>318</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>1824</td>\n",
       "      <td>5858.0</td>\n",
       "      <td>318</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>5</td>\n",
       "      <td>2004</td>\n",
       "      <td>5677.0</td>\n",
       "      <td>319</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>6</td>\n",
       "      <td>2196</td>\n",
       "      <td>5485.0</td>\n",
       "      <td>319</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>7</td>\n",
       "      <td>2421</td>\n",
       "      <td>5260.0</td>\n",
       "      <td>319</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>8</td>\n",
       "      <td>2631</td>\n",
       "      <td>5049.0</td>\n",
       "      <td>320</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>9</td>\n",
       "      <td>2864</td>\n",
       "      <td>4816.0</td>\n",
       "      <td>320</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>10</td>\n",
       "      <td>3136</td>\n",
       "      <td>4544.0</td>\n",
       "      <td>320</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>11</td>\n",
       "      <td>3380</td>\n",
       "      <td>4300.0</td>\n",
       "      <td>320</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>12</td>\n",
       "      <td>3632</td>\n",
       "      <td>4048.0</td>\n",
       "      <td>320</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>13</td>\n",
       "      <td>3864</td>\n",
       "      <td>3815.0</td>\n",
       "      <td>321</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>14</td>\n",
       "      <td>4126</td>\n",
       "      <td>3553.0</td>\n",
       "      <td>321</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>15</td>\n",
       "      <td>4407</td>\n",
       "      <td>3271.0</td>\n",
       "      <td>322</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>16</td>\n",
       "      <td>4651</td>\n",
       "      <td>3026.0</td>\n",
       "      <td>323</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>17</td>\n",
       "      <td>4907</td>\n",
       "      <td>2769.0</td>\n",
       "      <td>324</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>18</td>\n",
       "      <td>5137</td>\n",
       "      <td>2539.0</td>\n",
       "      <td>324</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>19</td>\n",
       "      <td>5331</td>\n",
       "      <td>2345.0</td>\n",
       "      <td>324</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>20</td>\n",
       "      <td>5530</td>\n",
       "      <td>2145.0</td>\n",
       "      <td>325</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>21</td>\n",
       "      <td>5722</td>\n",
       "      <td>1952.0</td>\n",
       "      <td>326</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>22</td>\n",
       "      <td>5935</td>\n",
       "      <td>1736.0</td>\n",
       "      <td>329</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>23</td>\n",
       "      <td>6154</td>\n",
       "      <td>1517.0</td>\n",
       "      <td>329</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>24</td>\n",
       "      <td>6322</td>\n",
       "      <td>1347.0</td>\n",
       "      <td>331</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>25</td>\n",
       "      <td>6450</td>\n",
       "      <td>1219.0</td>\n",
       "      <td>331</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>26</td>\n",
       "      <td>6561</td>\n",
       "      <td>1108.0</td>\n",
       "      <td>331</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>27</td>\n",
       "      <td>6677</td>\n",
       "      <td>992.0</td>\n",
       "      <td>331</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>28</td>\n",
       "      <td>6774</td>\n",
       "      <td>894.0</td>\n",
       "      <td>332</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>29</td>\n",
       "      <td>6876</td>\n",
       "      <td>792.0</td>\n",
       "      <td>332</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    person_INFECTED_LIGHT  person_HEALTHY  person_INFECTED_HARD\n",
       "t                                                              \n",
       "0                    1242          6440.0                   318\n",
       "1                    1369          6313.0                   318\n",
       "2                    1518          6164.0                   318\n",
       "3                    1672          6010.0                   318\n",
       "4                    1824          5858.0                   318\n",
       "5                    2004          5677.0                   319\n",
       "6                    2196          5485.0                   319\n",
       "7                    2421          5260.0                   319\n",
       "8                    2631          5049.0                   320\n",
       "9                    2864          4816.0                   320\n",
       "10                   3136          4544.0                   320\n",
       "11                   3380          4300.0                   320\n",
       "12                   3632          4048.0                   320\n",
       "13                   3864          3815.0                   321\n",
       "14                   4126          3553.0                   321\n",
       "15                   4407          3271.0                   322\n",
       "16                   4651          3026.0                   323\n",
       "17                   4907          2769.0                   324\n",
       "18                   5137          2539.0                   324\n",
       "19                   5331          2345.0                   324\n",
       "20                   5530          2145.0                   325\n",
       "21                   5722          1952.0                   326\n",
       "22                   5935          1736.0                   329\n",
       "23                   6154          1517.0                   329\n",
       "24                   6322          1347.0                   331\n",
       "25                   6450          1219.0                   331\n",
       "26                   6561          1108.0                   331\n",
       "27                   6677           992.0                   331\n",
       "28                   6774           894.0                   332\n",
       "29                   6876           792.0                   332"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bptk.plot_scenarios(\n",
    "    scenario_managers=[\"Covid19\"],\n",
    "    kind=\"area\",\n",
    "    title=\"Number Infected Persons\",\n",
    "    x_label=\"Days\",\n",
    "    y_label=\"Persons\",\n",
    "    scenarios=[\"base\"],\n",
    "    agents=[\"person\"],\n",
    "    agent_states=[\"HEALTHY\",\"INFECTED_HARD\",\"INFECTED_LIGHT\"],\n",
    "    return_df=True,\n",
    "    visualize_to_period = 30\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Finding the reproduction rate R0"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The second plot is the more interesting one. It helps us to figure find the solution of our question in the beginning. It describes how many agents one agent infects over a certain period of time, i.e. finding the reproduction rate `R0` of Covid-19. As shown in the plot below, the value for `R0` is under 0.15 person per day."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "bptk.plot_scenarios(\n",
    "    scenario_managers=[\"Covid19\"],\n",
    "    kind=\"area\",\n",
    "    title=\"Number Infected Persons Per Day\",\n",
    "    x_label=\"Days\",\n",
    "    y_label=\"Persons\",\n",
    "    scenarios=[\"base\"],\n",
    "    agents=[\"person\"],\n",
    "    agent_properties=[\"infected\"],\n",
    "    agent_property_types=[\"mean\"],\n",
    "    agent_states=[\"INFECTED_LIGHT\"],\n",
    "    visualize_to_period = 30\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The above plot gives us a roughly insight of the number of agents getting infected by one agent per day in average. With another feature of BPTK-Py, we can also look at the numbers in a table and compute the average value of `R0` over all days."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "jupyter": {
     "source_hidden": true
    }
   },
   "outputs": [],
   "source": [
    "r0_df = bptk.plot_scenarios(\n",
    "    scenario_managers=[\"Covid19\"],\n",
    "    kind=\"area\",\n",
    "    title=\"Number Infected Persons\",\n",
    "    x_label=\"Days\",\n",
    "    y_label=\"Persons\",\n",
    "    scenarios=[\"base\"],\n",
    "    agents=[\"person\"],\n",
    "    agent_properties=[\"infected\"],\n",
    "    agent_property_types=[\"mean\"],\n",
    "    agent_states=[\"INFECTED_LIGHT\"],\n",
    "    visualize_to_period = 30,\n",
    "    return_df=True\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "print(\"A person with Covid-19 infects around {} per day.\".format(r0_df.mean()[\"person_INFECTED_LIGHT_infected_mean\"]))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The following widget allows you to see how many people one person infects over a certain period of time. Looking at an interval of 20 days, one agent infects around 2 other agents."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "jupyter": {
     "source_hidden": true
    }
   },
   "outputs": [],
   "source": [
    "def output_text(x):\n",
    "    return \"A person with Covid-19 infects around {} persons in {} days.\".format(round((r0_df.mean()*x)[\"person_INFECTED_LIGHT_infected_mean\"]),x)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "interact(output_text, x=widgets.IntSlider(min=0, max=30, step=1, value=30));"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
